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The Better-Than-Average Effect in Comparative Self-Evaluation:
A Comprehensive Review and Meta-Analysis
Ethan Zell
University of North Carolina at Greensboro
Jason E. Strickhouser
Florida State University
Constantine Sedikides
University of Southampton
Mark D. Alicke
Ohio University
The better-than-average-effect (BTAE) is the tendency for people to perceive their abilities, attributes,
and personality traits as superior compared with their average peer. This article offers a comprehensive
review of the BTAE and the first quantitative synthesis of the BTAE literature. We define the effect,
differentiate it from related phenomena, and describe relevant methodological approaches, theories, and
psychological mechanisms. Next, we present a comprehensive meta-analysis of BTAE studies, including
data from 124 published articles, 291 independent samples, and more than 950,000 participants. Results
indicated that the BTAE is robust across studies (dz ⫽0.78, 95% CI [0.71, 0.84]), with little evidence
of publication bias. Further, moderation tests suggested that the BTAE is larger in the case of personality
traits than abilities, positive as opposed to negative dimensions, and in studies that (a) use the direct rather
than the indirect method, (b) involve many rather than few dimensions, (c) sample European Americans
rather than East-Asians (especially for individualistic traits), and (d) counterbalance self and average peer
judgments. Finally, the BTAE is moderately associated with self-esteem (r⫽.34) and life satisfaction
(r⫽.33). Results from selection model analyses clarify areas of the BTAE literature in which publication
bias may be of elevated concern. Discussion highlights theoretical and empirical implications.
Public Significance Statement
This meta-analysis reveals a robust tendency for people to perceive themselves as superior compared
with their average peer. This effect is more pronounced when examining personality traits than
abilities and is associated with higher self-esteem.
Keywords: better-than-average effect, positive illusions, self-enhancement, self-evaluation, social
comparison
When you look in the mirror, do you see a face that is above
average or below average in attractiveness? When you reflect upon
your intelligence or sociability, do you think that you are generally
superior or inferior to others? Answers to such questions are not
trivial. People with above average attractiveness, intelligence, and
sociability are wealthier than those who rank lower on these
dimensions (Judge, Hurst, & Simon, 2009;Sutin, Costa, Miech, &
Eaton, 2009). Nonetheless, evidence indicates that self-evaluations
are often distorted in a positive direction (Alicke & Sedikides,
2011;Dunning, 2005). Specifically, although only half the popu-
lation can be above average on a characteristic (except in the rare
circumstances in which distributions are negatively skewed), a
majority of people believe that they are above average. This
phenomenon, termed the better-than-average effect (BTAE), has
been documented across many socially valued dimensions (Alicke
& Govorun, 2005;Sedikides & Alicke, 2012). Although early
research on the BTAE primarily focused on testing its viability
(e.g., Brown, 1986), subsequent work has examined the motiva-
tional and cognitive mechanisms that contribute to it (Chambers &
Windschitl, 2004;Moore & Healy, 2008), the degree to which it
generalizes across demographic groups (Brown, 2010;Sedikides,
Gaertner, & Toguchi, 2003), its implications for psychological
well-being and adjustment (Sedikides & Gregg, 2008;Taylor &
Brown, 1988), and the domains in which it might be curtailed or
even reversed (Dunning, Meyerowitz, & Holzberg, 1989;Kruger,
1999).
This article was published Online First December 2, 2019.
XEthan Zell, Department of Psychology, University of North Carolina
at Greensboro; Jason E. Strickhouser, Department of Behavioral Sciences
and Social Medicine, Florida State University; Constantine Sedikides,
Department of Psychology, University of Southampton; Mark D. Alicke,
Department of Psychology, Ohio University.
Project materials are publicly available on the Open Science Framework
at https://osf.io/zpt82/?view_only⫽fc3213cbcdc3443bbb9f3f58db3fdc98.
Correspondence concerning this article should be addressed to Ethan
Zell, Department of Psychology, University of North Carolina at Greens-
boro, P.O. Box 26170, Greensboro, NC 27402. E-mail: e_zell@uncg.edu
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
Psychological Bulletin
© 2019 American Psychological Association 2020, Vol. 146, No. 2, 118–149
ISSN: 0033-2909 http://dx.doi.org/10.1037/bul0000218
118
The objective of the present article was to quantitatively aggre-
gate the vast BTAE literature in an effort to determine the effect’s
robustness and moderators. Despite several qualitative reviews of
the BTAE and related phenomena (Alicke & Govorun, 2005;
Chambers & Windschitl, 2004;Moore & Healy, 2008;Sedikides,
Gaertner, & Cai, 2015), no quantitative review of the BTAE
literature has been published. The lack of major research syntheses
on the BTAE is surprising, given its fundamental link to self-
related theories (Alicke & Sedikides, 2009;Sedikides & Alicke,
2019), and its prominence in social psychology textbooks (Kassin,
Fein, & Markus, 2017;Myers & Twenge, 2016). By synthesizing
the BTAE literature, this article seeks to provide an up-to-date
summary of what is known about the effect, in addition to iden-
tifying gaps that may spark future inquiry. Along these lines, we
first offer a conceptual overview of the BTAE, then present results
of a relevant meta-analysis, and finally, conclude by noting unre-
solved issues that may stimulate future research.
Better-Than-Average Effect in Self-Evaluation
Researchers in various disciplines, including social, personality,
clinical, health, industrial-organizational, and educational psychol-
ogy, as well as philosophers and neuroscientists, have long ques-
tioned the degree to which self-evaluations are biased, that is,
skewed in an overly positive or negative direction (Dunning,
Heath, & Suls, 2004;Ferris, Johnson, & Sedikides, 2018;Taylor &
Brown, 1988). Sometimes, self-evaluations can be compared with
objective criteria such as behavioral data, test scores, or expert-
appraisals (Mabe & West, 1982;Preuss & Alicke, 2009;Zell &
Krizan, 2014). However, many of the traits on which people
evaluate themselves, such as attractiveness, extraversion, or hon-
esty, lack an established, objective criterion. Moreover, even when
such objective measures exist, people may not have access to
them, may not appreciate their evidentiary value, or may outright
avoid them (Gramzow, 2011;Howell & Shepperd, 2012;
Sedikides, Green, Saunders, Skowronski, & Zengel, 2016). Thus,
rather than comparing self-judgments to results of objective tests,
researchers began to assess how people evaluate themselves in
relation to an average peer (Weinstein, 1980,1982). By definition,
the average person in a given sample should believe that they rank
average, barring unusual circumstances (i.e., a skewed distribu-
tion). If, however, the average person thinks that they are above
average, one can argue that a directional bias exists such that
people generally evaluate themselves in an unrealistically favor-
able manner.
Definitions and Distinctions
We define the BTAE as the proclivity to rate one’s current
abilities, attributes, or personality traits more favorably than those
of the average peer. Broadly, the BTAE is considered a prominent
manifestation of self-evaluation bias (Kwan, John, Kenny, Bond,
& Robins, 2004;Moore & Healy, 2008). Related research on
unrealistic optimism indicates that people believe positive out-
comes are more likely and negative outcomes are less likely to
happen to them (vs. others) or than objective base-rates would
attest (Shepperd, Klein, Waters, & Weinstein, 2013). Unrealistic
optimism studies overlap methodologically with the BTAE in that
they often examine self-evaluations in relation to an average other.
However, whereas unrealistic optimism research focuses on judg-
ments of what may happen in the future, BTAE research focuses
on judgments regarding one’s current abilities, attributes, or traits.
Thus, unrealistic optimism is distinguishable from the BTAE in
that the former addresses the perceived likelihood of future events,
whereas the latter addresses present self-perceptions, which may
be key correlates of future behavior and life choices (Swann,
Chang-Schneider, & Larsen McClarty, 2007).
The BTAE can also be distinguished from other self-evaluation
biases. For example, individuals sometimes exhibit illusions of
control, where they believe they can control random outcomes
(Thompson, 1999). Additionally, research has found robust sup-
port for a holier than thou effect, where the percentage of individ-
uals who estimate they would engage in a moral behavior is
significantly higher than the percentage of those who actually
behave morally when confronted with the same situation in real
life (Epley & Dunning, 2000). Although these findings suggest
that people overestimate their control over random events and
moral behavior, they do not directly test perceptions of self in
relation to others as does BTAE research. Finally, several studies
on the Dunning-Kruger effect show that people overestimate the
rank of their performance, especially when they occupy an inferior
position in the performance distribution (Dunning, 2011). These
findings are consistent with the BTAE, but, whereas Dunning-Kruger
effect studies compare self-perceptions of performance on a specific
test (e.g., a math test) with objective test scores, BTAE studies
compare self-perceptions on attribute, ability, or trait dimensions (e.g.,
math ability or competence) with perceptions of the average person.
In summary, although the BTAE can be considered one of several
manifestations of self-evaluation bias, the effect is unique in its
emphasis on comparative evaluations of the present self on relatively
enduring attribute, ability, or trait dimensions.
Finally, the BTAE can be distinguished from research on self-
esteem, which is defined as the degree to which people have
positive versus negative evaluations of themselves, both in specific
domains and as a whole (Leary & Baumeister, 2000). Consistent
with the BTAE, large multinational studies have found that Euro-
pean Americans typically evaluate themselves favorably on self-
esteem measures (Diener & Diener, 1995). However, whereas
self-esteem research assesses self-evaluation, BTAE research exam-
ines how people evaluate themselves in comparison to their average
peer. A popular measure of trait self-esteem, the Rosenberg (1965)
Self-Esteem Scale, does include two items in which people evaluate
themselves comparatively (i.e., I am able to do things as well as most
other people and I feel that I’m a person of worth, at least on an equal
plane with others). Nonetheless, these items assess whether people
perceive themselves as equal to others (i.e., adequate) and not whether
people perceive themselves as superior.
Theoretical Perspectives
Truth and Bias Model. Psychologists have long been inter-
ested in the degree to which accuracy and bias characterize social
perception (Brunswik, 1955;Fletcher & Kerr, 2010). Along these
lines, the Truth and Bias Model (West & Kenny, 2011) proposes
that social perception is influenced by a truth force that pulls
judgments toward reality and a bias force that pull judgments away
from reality. Many variables may contribute to truth and bias
forces, with some having a relatively strong and others a relatively
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119
BETTER-THAN-AVERAGE EFFECT
weak influence. In addition, bias variables may have either a high
or low bias value, in which they pull judgments toward the positive
or negative pole of the judgment scale, respectively. Critically, the
Truth and Bias Model specifies that the relation between accuracy
(i.e., the degree to which social perceptions are correlated with or
track reality) and bias (i.e., mean-level differences between social
perceptions and reality) is complex. Sometimes bias and accuracy
are inversely related, as was previously assumed in the social
perception literature, but there are also situations in which accu-
racy and bias are unrelated or even positively related. Thus, the
presence of an overall directional bias in social judgment does not
necessarily imply that these judgments are inaccurate; that is, bias
can occur alongside near-perfect rank order accuracy.
Although most research inspired by the Truth and Bias Model
pertains to the perception of other people, such as one’s romantic
partner (Stern & West, 2018), the model also delineates how the
BTAE may occur in self-judgment. Presumably, people desire
realistic views of themselves, as highly distorted self-beliefs could
lead to maladaptive decisions or behaviors. However, several
motivational and nonmotivational variables, described in greater
detail below, may substantially bias self-views, often in a positive
direction (i.e., have a high bias value). The end result of these
competing forces is an overall directional bias, whereby people
evaluate themselves somewhat more favorably than is objectively
warranted. Taken together, the Truth and Bias Model provides a
framework for understanding the cumulative influence of truth and
bias forces on self-judgment, and suggests that biased self-beliefs
can in some contexts reflect reasonably accurate self-views.
Self-enhancement. Self-enhancement theories propose that
people have positively distorted, but not grandiose, perceptions of
self across judgment domains, and engage in various strategies to
promote or maintain these beliefs (Alicke & Sedikides, 2009;
Sedikides & Alicke, 2019). Evidence for self-enhancement has
been obtained in many contexts. For example, people perceive
themselves more favorably than do dispassionate observers, more
often discount negative than positive feedback about themselves,
better remember positive than negative information about their
past, and prefer to interact with others who view them favorably as
opposed to unfavorably (Hepper, Gramzow, & Sedikides, 2010;
Hepper, Sedikides, & Cai, 2013;Zell & Alicke, 2010). The BTAE
is fundamental to self-enhancement theories, given that it is per-
haps the longest and most frequently studied manifestation of
self-enhancement in the literature. Thus, understanding the size
and consistency of the BTAE across studies is critical in eval-
uating the degree to which extant findings broadly support
self-enhancement theories.
Self-verification. Self-verification theory asserts that people
prefer feedback and relationship partners who affirm rather than
challenge their self-views (Swann, 2012;Swann & Buhrmester,
2012), and clarifies how the BTAE may emerge in development.
Specifically, secure attachment figures may provide messages that
instill positive self-beliefs in childhood (Cassidy, 1988). Then,
selective socialization with people who affirm positive self-views
may polarize and strengthen such views, thus leading people to
view themselves as superior. Moreover, social norms pressure
people to refrain from communicating negative feedback to both
acquaintances and close others, which may further strengthen
self-superiority beliefs (Fay, Jordan, & Ehrlinger, 2012;Tesser &
Rosen, 1975). Therefore, self-verification theory suggests that
biased self-views arise not only from self-enhancement processes,
but also from selective exposure to information that creates and
ultimately strengthens these beliefs. Consistent with this argument,
the BTAE is more pronounced among those with high versus low
self-esteem (e.g., Bosson, Swann, & Pennebaker, 2000;Chung,
Schriber, & Robins, 2016), presumably because high (low) self-
esteem engages people to seek information that confirms unreal-
istically positive (negative) self-views.
Social comparison. Social comparison theories posit that
people consider their standing in relation to relevant peers during
self-evaluation, especially for traits that lack objective definition
(Festinger, 1954;Suls & Wheeler, 2017;Wood, 1989). Early
social comparison research focused primarily on comparisons with
discrete individuals, but later work recognized that comparisons
may also occur with abstract targets such as the average person in
one’s school or country (Buckingham & Alicke, 2002). A key
question in the social comparison literature is whether and when
people tend to focus on upward comparisons with superior others
or downward comparisons with inferior others. A meta-analytic
review of the social comparison literature demonstrated that peo-
ple more often choose upward than downward comparison stan-
dards for the purposes of self-appraisal (Gerber, Wheeler, & Suls,
2018), but these data do not address whether people generally
evaluate themselves as superior, inferior, or comparable to their
peers. The BTAE literature addresses this gap. If people typically
view themselves as above average, this would suggest that down-
ward comparisons are more dominant in perceptions of self than
upward comparisons. Thus, research on the BTAE may be used to
address a key question in social comparison theory regarding
the salience of upward versus downward comparisons in self-
evaluation.
Self-knowledge. Theoretical perspectives on self-knowledge
posit that self-evaluations are prone to error and bias (Dunning,
2005;Wilson, 2002). Along these lines, hundreds of accuracy
studies have examined the correlation between self-evaluations of
ability and objective ability measures, such as standardized tests
and supervisor ratings (Freund & Kasten, 2012;Mabe & West,
1982). A quantitative synthesis of 22 meta-analyses, spanning a
variety of domains such as academic ability, intelligence, medical
skills, sports ability, and vocational skills, found that the average
association between self-evaluations of ability and objective per-
formance measures is only moderate (r⫽.29; Zell & Krizan,
2014). Further, evidence has established that self-ratings of per-
sonality are moderately to strongly correlated with, but not iden-
tical to, peer-ratings of personality (Vazire, 2010;Vazire &
Carlson, 2010). Nonetheless, it remains unclear from these
correlational studies whether self-evaluations are typically more
positive or more negative than other indices suggest they should
be. Unlike research on accuracy, research on the BTAE is focused
on identifying whether and to what extent self-evaluations are
generally biased in a positive or negative direction. Therefore, the
BTAE literature is crucial in addressing the general question of
how well people know their abilities, attributes, and personalities
(Dunning et al., 2004).
Methodological Approaches
Research evaluating the BTAE in comparative self-evaluation
has used one of four methods (see Figure 1). First, research using
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120 ZELL, STRICKHOUSER, SEDIKIDES, AND ALICKE
the direct method has participants evaluate themselves in compar-
ison to the average person on a rating scale. Given that the scale
midpoint represents the average person, mean responses that differ
from the midpoint in a favorable direction indicate a BTAE. In a
representative study, for example, college students evaluated
themselves relative to the average same-gender college student on
20 positive (e.g., dependable, considerate) and 20 negative (e.g.,
meddlesome, insecure) personality traits using 7-point scales that
ranged from much less to much more, with a midpoint of about the
same (Alicke, Klotz, Breitenbecher, Yurak, & Vredenburg, 1995,
Study 1). Consistent with the BTAE, participants rated positive
traits as more descriptive and negative traits as less descriptive of
themselves than the average student. In a similar study, high
school students rated positive traits as more descriptive and neg-
ative traits as less descriptive of themselves than the average
student at their school of the same age and gender (Hoorens,
1995). Beyond personality, other studies using the direct method
have found a BTAE for a variety of attributes and abilities,
including intelligence, leadership, physical attractiveness, and mo-
rality (Pelham & Swann, 1989;Sedikides, Meek, Alicke, & Tay-
lor, 2014;Van Lange & Sedikides, 1998).
Second, research using the indirect method has participants
evaluate themselves and the average person on separate scales.
Mean differences between self-ratings and average-ratings are then
calculated across participants to determine whether participants
generally rated themselves as above or below average. In a pio-
neering study, college students evaluated themselves and the av-
erage peer on 154 personality traits using 7-point scales that
ranged from not at all characteristic to very characteristic (Alicke,
1985). Consistent with the BTAE, participants rated desirable
personality traits as more characteristic and undesirable personal-
ity traits as less characteristic of themselves than the average
student. In a related study, college students rated positive trait
adjectives as more representative and negative trait adjectives as
less representative of themselves than of most others (Brown,
1986). Moreover, later studies found that people rate their abilities,
such as intelligence (Kruger, 1999, Study 2) and driving skill
(Walton, 1999), more favorably than the average person’s abilities.
Third, research using the forced choice method has participants
indicate whether they rank above or below average on a given
dimension. Assuming a normal distribution, about 50% of respon-
dents should rank above average and about 50% should rank below
average. Thus, if significantly more than 50% of respondents think
they rank above average, a BTAE is said to have occurred. Along
these lines, an oft-cited study found that, among a sample of
one-million SAT test takers, most students believed that they were
above average in athleticism (60%), leadership (70%), and the
ability to get along with others (85%; College Board, 1976-1977;
as described in Alicke & Govorun, 2005). Moreover, a survey of
faculty at the University of Nebraska found that 94% rated them-
selves as above average teachers (Cross, 1977).
Fourth, research using the percentile method has participants
indicate the percentage of people who rank as good as or worse
than them on a given dimension. Given that the scale midpoint
(i.e., the 50th percentile) represents the median rank, as well as the
average rank in a normal distribution, mean responses that are
significantly higher than the 50th percentile are interpreted as
support for the BTAE. A classic study using this method found that
American and Swedish college students rated their driving safety
and skill as significantly higher than the 50th percentile relative to
other students at their university (Svenson, 1981). In addition, later
work found that college students rated their personality traits (e.g.,
neat, sensitive) as above the 50th percentile relative to other
students at their university (Dunning et al., 1989, Study 1). Of the
four methods, results from the percentile method most unambig-
uously indicate a self-evaluation bias, as only 50% of people can
be above the median. Conversely, with methods that invoke com-
parisons with an average peer, more than 50% can be above
average in a skewed distribution.
Figure 1. Methods used to assess comparative self-evaluation, with sample responses indicative of a better-
than-average-effect (BTAE) in judgments of math ability.
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121
BETTER-THAN-AVERAGE EFFECT
Taken together, research using direct, indirect, forced-choice,
and percentile methods has provided consistent support for the
BTAE and inspired dozens of studies that further explored the
nature and robustness of the effect. Having established key meth-
ods used to assess the BTAE, we next discuss explanations for the
effect.
Underlying Mechanisms
The BTAE derives from motivational factors such as a motive to
perceive or present the self favorably. Nonetheless, the BTAE is
more than merely a motivational phenomenon. Indeed, like many
robust social psychological phenomena, the BTAE reflects the
influence of several distinct mechanisms. Although a detailed
discussion of each mechanism is beyond the scope of this report,
we summarize below the empirical backing for both motivational
and cognitive contributors to the BTAE.
Motivational mechanisms. Evidence indicates that people
are motivated to perceive themselves favorably and that this desire
for positive self-beliefs partly underlies the BTAE (Alicke &
Govorun, 2005;Sedikides & Alicke, 2019;Sedikides et al., 2015).
Consistent with the motivational perspective, the BTAE is larger
for positive traits and weaker for negative traits that are perceived
as controllable (Alicke, 1985), perhaps because people are moti-
vated to attribute their strengths to internal factors (e.g., effort,
ability) and their weaknesses to external factors (e.g., fate). In
addition, the BTAE is more pronounced in the case of abstract
dimensions (Dunning et al., 1989), vague dimensions (Logg, Ha-
ran, & Moore, 2018), as well as dimensions that lack external
verification (Van Lange & Sedikides, 1998), presumably because
people define these dimensions in an idiosyncratic and self-serving
manner. Finally, the BTAE is larger for traits that are perceived as
both personally important (Brown, 2012) and culturally important
(Sedikides et al., 2003), perhaps because these traits are of greater
motivational significance than unimportant traits.
Beyond examining differences in the BTAE based on trait
importance, one experiment found that the BTAE was more pro-
nounced among participants who received negative feedback about
their intelligence than participants who received no feedback
(Brown, 2012, Study 5). These data suggest that a motive to
promote or protect the self directly contributes to the BTAE.
Another set of studies found that comparative ratings of the aver-
age person in relation to the self (How honest is the average
student in comparison to you?) are more favorable than absolute
ratings of the average person (How honest is the average student?),
and that this tendency to assimilate the average person to the self
is more pronounced in the case of undesirable than desirable traits
(Guenther & Alicke, 2010). These studies indicate that people
assimilate the average person to the self during comparative judg-
ment, but that self-enhancement concerns restrict the amount of
assimilation for traits that are motivationally significant.
Additional support for the role of motivational mechanisms
comes from work demonstrating that the BTAE continues to occur
even when people are under cognitive load (Alicke et al., 1995,
Study 7), which precludes deliberative thought about the self and
others required for most cognitive explanations. Moreover, people
continue to rate themselves as above average even when the
average person is assigned a value that participants had previously
selected for themselves (Alicke, Vredenburg, Hiatt, & Govorun,
2001). These data, as well as the fact that the BTAE occurs when
people are quickly rating themselves on many traits, suggest that
the BTAE cannot be fully explained in terms of biased recruitment
or information processing about the self and others. Conversely,
people may simply invoke an “I am better than average” heuristic
when responding to comparative self-evaluation items (Alicke &
Govorun, 2005), and this heuristic may be grounded in a functional
motive to perceive the self as a positive, capable, and moral person
(Fiske, 2014;Leary, 2007).
We argue that self-enhancement provides a parsimonious expla-
nation for results suggesting motivational influences on the BTAE.
However, self-verification theory (Swann, 2012) provides an im-
portant alternative explanation for several of these effects. Specif-
ically, the BTAE may be stronger for positive and important traits
because self-beliefs for these traits are held with greater certainty
(Pelham & Swann, 1989), and people are more likely to seek
confirmatory information for certain than uncertain self-views.
Moreover, the BTAE may be stronger following negative feedback
because feedback that conflicts with self-views triggers compen-
satory self-verification processes whereby people selectively acti-
vate or pursue positive information about themselves (Swann &
Brooks, 2012). Lastly, cognitive load may both increase self-
enhancement and decrease self-verification (Hixon & Swann,
1993), complicating explanations for cognitive load effects on the
BTAE. Thus, although more research is needed to tease apart these
competing explanations, it appears that both self-enhancement and
self-verification strivings may contribute to biased self-beliefs.
Cognitive mechanisms. Research also suggests that several
cognitive variables contribute to the BTAE and related phenomena
(Chambers & Windschitl, 2004;Moore & Healy, 2008). The most
prominent nonmotivational contributor to the BTAE is egocen-
trism, or the tendency for people to overweight their own charac-
teristics and underweight the characteristics of the average person
when judging themselves in comparison to the average person.
This undue focus on the self leads people to perceive themselves
as above average on relatively common dimensions in which they
perceive themselves favorably, but below average on relatively
rare dimensions in which they perceive themselves unfavorably
(e.g., juggling, computer programming; Kruger, 1999;Zell &
Alicke, 2011). Further, judgments of the self in comparison with
the average person are more strongly associated with, and more
similar to, absolute judgments of the self than absolute judgments
of the average person (Guenther & Alicke, 2010;Klar & Giladi,
1999). Egocentrism may occur, often rationally, because people
know more about themselves than their average peer and thus rely
upon this richer information source during judgment (Moore &
Healy, 2008).
A related explanation, termed focalism, states that people over-
emphasize the characteristics and abilities of the focal object
during comparative judgment, which in most cases is the self. That
is, research on the BTAE often uses response scales in which the
self is the target of evaluation and is therefore more focal than the
average person (How honest are you in comparison to the average
person?). Consistent with the focalism account, research indicates
that the BTAE is reduced when the average person is placed in the
focal position (How honest is the average person in comparison to
you?) than when the self is placed in the focal position, as is
customary in BTAE studies (Pahl & Eiser, 2005,2007).
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122 ZELL, STRICKHOUSER, SEDIKIDES, AND ALICKE
Lastly, a third explanation, termed the generalized-group ac-
count, states that the BTAE occurs because people often view
individuated objects such as the self or another person more
favorably than generalized objects such as the average group
member. Consistent with this explanation, people perceive other
individuals, such as their romantic partner (Brown & Han, 2012),
their child (Lench, Quas, & Edelstein, 2006), and even randomly
selected strangers, as above average (Klar, 2002). The results of
such studies indicate that the BTAE may occur because individu-
ated entities, like the self, are regarded more favorably than ag-
gregated entities, like the average person.
Nonetheless, egocentrism, focalism, and generalized-group ac-
counts do not completely explain the BTAE. That is, the BTAE
remains even when researchers use response scales that obviate
egocentrism and focalism, such as when self-evaluations and
average-evaluations are made on separate scales as in the indirect
method. Additionally, although people perceive most any individ-
ual as above average, people perceive themselves as superior to
specific individuals as well as to group aggregates (Alicke et al.,
1995;Krizan & Suls, 2008;Sedikides & Alicke, 2012).
Caveats and Critiques
A critique of research on the BTAE is that some people who
perceive themselves as above average are in fact, above average.
For example, it would be unsurprising if Serena Williams per-
ceived herself as above average in athleticism, as she is in fact far
above average. However, the majority of people overestimate their
personality and ability when self-perceptions are compared to
objective measures of these constructs (Heck & Krueger, 2015).
Furthermore, people who rank in the first quartile (0 –24th percen-
tile) and second quartile (25th– 49th percentile) on performance
tests tend to think erroneously that their performance ranks signif-
icantly above average (Dunning, 2011). Thus, many people who
perceive themselves as above average are not actually above
average. Nonetheless, it is important to recognize that the BTAE
reflects a bias at the group as opposed to the individual level, and
that not all individuals who perceive themselves as above average
are necessarily in error (Moore, 2007).
According to another critique, individuals simply state publicly
that they are above average, while privately recognizing that they
are not. Although self-presentational concerns may exacerbate
self-enhancement effects (Tyler & Rosier, 2009), individuals who
believe that they are above average are willing to bet money that
they will rank superior to others on objective tests (Williams &
Gilovich, 2008). Moreover, offering financial incentives for unbi-
ased self-appraisal fails to eliminate self-enhancement effects in
performance prediction (Ehrlinger, Johnson, Banner, Dunning, &
Kruger, 2008). Hence, individuals seem genuinely to believe that
they are above average. Moreover, implicit tests that are less
susceptible to socially desirable responding illustrate that individ-
uals more quickly associate positive concepts and less quickly
associate negative concepts with the self than with others (Kar-
pinski, 2004). These implicit tests provide further support for the
notion that self-superiority beliefs are genuine.
Finally, although we propose that the BTAE reflects biased (i.e.,
unrealistically positive) self-beliefs, this bias may result from
mechanisms that are at least partly rational. People receive mostly
positive feedback about themselves throughout life (Swann, 2012),
many of the dimensions in which people evaluate themselves are
ambiguous and therefore open to interpretation (Dunning et al.,
1989;Logg et al., 2018), and people often evaluate themselves
under conditions in which motivation or cognitive resources are
low (Alicke et al., 1995). Therefore, the BTAE may predictably
result from incomplete or biased information that people receive
about themselves, idiosyncratic definitions of trait dimensions, or
heuristics that culminate in somewhat biased estimates of one’s
attributes and abilities while preserving limited cognitive resources
for other pursuits.
The Current Meta-Analysis
Building upon prior narrative reviews of the BTAE, which have
focused primarily on underlying mechanisms (Alicke & Govorun,
2005;Chambers & Windschitl, 2004;Moore & Healy, 2008;
Sedikides & Alicke, 2012,2019), the present article used meta-
analysis to synthesize research on the BTAE. In doing so, we
addressed several core questions about the effect, including (a) its
magnitude and robustness, (b) the degree to which it is moderated
by demographic variables and measurement characteristics, and (c)
the extent to which it is associated with measures of psychological
well-being.
Magnitude and Robustness
The BTAE is widely considered to be a highly robust effect—in
fact, social psychology instructors often administer direct mea-
sures of the BTAE as a relatively foolproof demonstration of
self-enhancement (Guenther & Alicke, 2010). However, it is not
known whether the effect is consistent and robust across studies.
Further, little is known about the overall magnitude of the BTAE.
It is both practically and theoretically important to understand the
overall size of the BTAE, as a large effect would indicate that
people have substantially biased perceptions of themselves.
Potential Moderators
Method. As indicated above, the BTAE is typically studied
using four methods: direct, indirect, forced-choice, and percentile.
Research on unrealistic optimism, a phenomenon related to the
BTAE, found larger self-enhancement effects with the direct
method versus the indirect method (Otten & Van Der Pligt, 1996),
likely because egocentrism and focalism are minimized when
using the indirect method. However, it remains unclear whether
the BTAE is also larger when examining the direct versus the
indirect method. Further, little is known about the relative size of
the BTAE in studies that use forced-choice or percentile methods.
The forced-choice method may yield relatively large estimates
of the BTAE, given that participants are required to choose among
two extreme options and may select the option that best matches
their self-view. Conversely, the percentile method may yield rel-
atively small effects, as its flexible response format allows for the
identification of participants with moderate yet still favorable
self-views (e.g., someone who places themselves at the 52nd
percentile).
In addition to comparing the BTAE across the four major
methods, we examined whether the effect varied as a function of
other methodological choices. Specifically, we tested whether di-
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123
BETTER-THAN-AVERAGE EFFECT
rect method studies yield larger effects when they explicitly label
the scale midpoint as average, and we tested whether indirect
method studies yield larger effects when they counterbalance self
and average other judgments. We did not formulate strong predic-
tions regarding the potential effect of midpoint labels and judg-
ment counterbalancing on the BTAE.
Judgment domain. Whereas many BTAE studies have par-
ticipants evaluate themselves on personality traits (e.g., kindness,
sensitivity), others have participants evaluate their abilities (e.g.,
math or verbal ability). Given that personality traits are typically
more abstract and less subject to external verification than ability
dimensions (Dunning et al., 1989;Van Lange & Sedikides, 1998),
we anticipated that the BTAE would be larger for personality traits
than abilities. Further, consistent with prior work on egocentrism
(Kruger, 1999;Zell & Alicke, 2011), we anticipated that a BTAE
would occur for relatively easy abilities, but that a worse-than-
average effect (WTAE) would occur for relatively hard abilities.
This variation in the magnitude of the BTAE by ability difficulty
likely occurs because people overemphasize their own abilities and
neglect the abilities of others’ during comparative judgment (i.e.,
egocentrism).
Another critical issue in the BTAE literature is the valence of
the judgment dimension. Whereas many BTAE studies focus on
positive dimensions (e.g., kind, sensitive), other studies focus on
negative ones (e.g., unkind, insensitive), or include both. A BTAE
on positive dimensions is viewed as a manifestation of self-
enhancement or an exaggeration of one’s favorable qualities, but a
BTAE on negative dimensions is viewed as a manifestation of
self-protection or a minimization of one’s unfavorable qualities
(Krueger & Wright, 2011). Presently, it remains unclear whether
self-enhancement generally exerts a stronger motivational force
than self-protection. Thus, by examining overall differences in the
BTAE as a function of trait valence, the meta-analysis allowed for
a novel comparison of these two fundamental self-motives.
Finally, prior research on the BTAE varies in the number of
dimensions explored, with some studies having participants eval-
uate themselves on a single dimension (e.g., math ability; Mattern,
Burrus, & Shaw, 2010) and others on dozens of dimensions
(Alicke, 1985). People may engage in effortful cognitive strate-
gies, such as thinking deeply about their own and others’ experi-
ences in the domain, when rating themselves on a single dimen-
sion. Alternatively, people may simply adopt an “I am better than
average” heuristic when rating themselves across many dimen-
sions in an effort to conserve cognitive resources. Thus, one might
expect the BTAE to be larger in studies that had participants
evaluate themselves along many as opposed to few dimensions.
Sample characteristics. Self-enhancement theories argue that
the desire for positive self-regard is universal, and therefore predict
that the BTAE should obtain regardless of the particular country or
culture being studied (Brown, 2010;Sedikides et al., 2015). Al-
though initial evidence for the BTAE was obtained primarily in
Western Individualist societies, later studies found evidence con-
sistent with the BTAE in a variety of countries and cultures
(Loughnan et al., 2011), including Eastern Collectivist societies
such as China (Wu, 2018), Japan (Brown & Kobayashi, 2002), and
Korea (Lee, 2012), despite modesty norms in these societies.
Further, a meta-analysis of seven studies indicates that self-
enhancement, defined broadly to include the BTAE and unrealistic
optimism, is magnified in culturally relevant domains (Sedikides,
Gaertner, & Vevea, 2005; see also, Gebauer, Sedikides, &
Schrade, 2017). For example, the BTAE is larger for European
Americans on individualistic traits (e.g., independent, unique), and
larger for East Asians on collectivistic traits (e.g., cooperative,
loyal; Sedikides et al., 2003). In sum, these data suggest that the
BTAE is universal, but depends on the nature of the dimension
assessed. Thus, differences in the magnitude of the BTAE across
cultures may be driven by variations in the cultural importance of
certain traits as opposed to culture per se.
Lastly, although most studies of the BTAE have been conducted
on convenience samples of college students, the effect has also
obtained in nationally representative samples of Americans (Heck,
Simons, & Chabris, 2018;Stark & Sachau, 2016), and in college
professors (Cross, 1977), MTurk workers (Howell & Ratliff, 2017,
Study 2), prisoners (Sedikides et al., 2014), and truck drivers
(Walton, 1999), among other groups. Thus, in the present work we
examined whether the BTAE is larger in college student samples,
who are typically studied in this literature, than in other samples.
For exploratory purposes, we also examined the degree to which
the BTAE varies as a function of other demographic variables
including age, gender, and race/ethnicity. Based on prior work
suggesting that narcissism, a personality variable defined by gran-
diose perceptions of self, is greater in men versus women (Grijalva
et al., 2015), African Americans versus Caucasian Americans
(Zeigler-Hill & Wallace, 2011), and young people versus older
people (Foster, Campbell, & Twenge, 2003), we assessed whether
the BTAE shows similar patterns.
Referent characteristics. Some studies on the BTAE have
participants evaluate themselves in comparison with a general
referent such as the average person (Eriksson & Funcke, 2014),
whereas others use a more specific referent such as the average
person of the same age, gender, and school as the participant (Lee,
2012). General referents provide more latitude for self-serving
interpretations of the referent that might boost the BTAE (Dunning
et al., 1989). However, people may be more motivated to perceive
themselves as superior to specific referents, given their greater
similarity to the self and self-relevance (Tesser, 1988). Provided
these divergent possibilities, we did not formulate strong predic-
tions about the influence of referent specificity on the BTAE.
Psychological well-being. Some scholars proposed that the
BTAE and other related phenomena, collectively termed positive
illusions, are more prevalent among psychologically healthy ver-
sus unhealthy individuals (i.e., people with depression or low
self-esteem; Taylor & Brown, 1988), whereas others have argued
that self-enhancement is associated with worse mental health (Col-
vin, Block, & Funder, 1995). To address this debate, a recent
meta-analysis evaluated whether self-enhancement is differentially
associated with personal adjustment (i.e., life satisfaction, positive
affect, and low negative affect) than interpersonal adjustment (i.e.,
how favorably people are evaluated by others; Dufner, Gebauer,
Sedikides, & Denissen, 2019). This meta-analysis reported a
small-to-moderate association between self-enhancement and
personal adjustment, but a near-zero association between self-
enhancement and interpersonal adjustment. Critically, self-
enhancement was defined broadly in this work to include more
than 25 measures besides the BTAE, with only a few included
studies focusing on the BTAE in particular. Thus, the degree to
which the BTAE specifically predicts psychological adjustment is
unresolved.
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124 ZELL, STRICKHOUSER, SEDIKIDES, AND ALICKE
Method
Research materials for this project, including a full dataset and
complete list of databases and search terms, are publicly available
on the Open Science Framework at https://osf.io/zpt82/?view_
only⫽fc3213cbcdc3443bbb9f3f58db3fdc98.
Article Identification
Literature search. We conducted a search of electronic da-
tabases (e.g., PsycINFO, PsycARTICLES, CINHAHL, ERIC, and
SocINDEX) to identity articles on the BTAE. Search terms in-
cluded better than average effect, above average effect, self-
enhancement effect, comparative bias, and positive illusions. We
identified additional articles by scanning the reference lists of
included articles and major reviews of research on the BTAE or
self-enhancement more broadly (i.e., Alicke & Govorun, 2005;
Chambers & Windschitl, 2004;Dufner et al., 2019;Moore &
Healy, 2008;Sedikides et al., 2015).
Inclusion and exclusion criteria. To be included in the meta-
analysis, articles had to meet the following criteria: (a) be acces-
sible online or through interlibrary loan, (b) be written in English,
(c) be a published, empirical article that reports primary empirical
data, (d) include an evaluation of one’s current abilities, attributes,
or traits either in comparison to or in addition to an evaluation of
an average peer on the same dimensions, and (e) provide an effect
size, or sufficient information to determine an effect size, indexing
the magnitude of the BTAE in any age group (see Figure 2). We
restricted our analysis to published articles, given that inclusion of
the enormous bank of unpublished data sets (consisting mostly of
classroom demonstrations) was unfeasible. We defined abilities,
attributes, and traits broadly to incorporate any competency (e.g.,
academic ability, athleticism, social skill), personal characteristic
(e.g., health, physical attractiveness), or personality dimension
(e.g., considerate, friendly) studied in prior research.
Based on these criteria, we excluded studies that examined
comparative judgments for future outcomes (i.e., unrealistic opti-
mism;Shepperd et al., 2013) and likelihood to engage in a moral
behavior (i.e., holier than thou beliefs;Epley & Dunning, 2000). In
addition, we excluded studies that contrasted comparative judg-
ments of performance on a specific test with objective tests scores
(Burson, Larrick, & Klayman, 2006), because this reflects a dif-
ferent index of self-enhancement. Finally, given our focus on
comparative self-evaluations in relation to an average peer, we
excluded studies that examined comparative self-evaluations in
relation to one or a few specific others (Krizan & Suls, 2008)as
well as studies that examined comparative evaluations of a target
besides the self in relation to the average person (Klar, 2002).
After exclusions, a total of 124 published articles that examined
the BTAE in comparative self-evaluations remained (see Appen-
dix A for article details). These articles collectively provided effect
sizes from 291 independent samples and 965,307 participants. We
note that five studies contributed disproportionately to the over-
all sample size. Specifically, two studies provided results from
805,708 participants (Mattern et al., 2010), two studies provided
results from 98,633 participants (Howell & Ratliff, 2017), and one
study provided results from 15,806 participants (Kuyper, Dijkstra,
Buunk, & Van der Werf, 2011). The overall sample size excluding
these five unusually large studies was 45,160 across 286 indepen-
dent samples (average n⫽157.90). Given the imbalance in sample
sizes, our primary analyses used random-effects models, which are
less influenced by large studies than are fixed-effect models (Bo-
renstein, Hedges, Higgins, & Rothstein, 2009a).
Obtaining Effect Sizes
The BTAE is assessed either by having people rate themselves
relative to others on a single scale (i.e., the direct, forced-choice,
and percentile methods) or rate themselves and the average person
on separate scales (i.e., the indirect method). Given that the BTAE
is evaluated using a single group of participants, within-subjects
approaches are necessary to estimate its size. Here, we assessed the
magnitude of the BTAE using Cohen’s dz (Cohen, 1988;Lakens,
2013), which represents the standardized difference between a
mean and a specified value. When ratings of the self and the
average person are made on the same scale, dz is operationalized
as the standardized difference between self-ratings and the scale
midpoint ([M
judgment
⫺Midpoint]/SD
judgment
), with the midpoint
being assigned either to the middle value on a rating scale, the 50th
percentile, or the middle value in between two options for direct,
percentile, and forced-choice methods, respectively. When sepa-
rate scales are used as in the indirect method, dz is operationalized
as the standardized difference between self-ratings and average
ratings; M
difference
/SD
difference
. Thus, dz provides a common metric
that can be used for BTAEs derived from single-scale and two-
scale approaches. Consistent with Cohen’s dcommonly reported
in between-subjects studies, we interpreted dz values using the
following rubric: 0.20 ⫽small, 0.50 ⫽medium, 0.80 ⫽large.
We extracted from each article effect sizes in the form of dz
(total k⫽310) using several strategies. First, a few articles directly
reported dz (k⫽7). Second, we derived effect sizes from single-
scale approaches (i.e., direct, forced-choice, and percentile meth-
Figure 2. Flowchart for the article search. BTAE ⫽better-than-average-
effect.
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125
BETTER-THAN-AVERAGE EFFECT
ods; k⫽199) using t-statistics gauging the BTAE, dz ⫽t/公(N),
or means and standard deviations for comparative self-judgments,
dz ⫽(M⫺Midpoint)/SD. Third, we derived effect sizes from
two-scale approaches (i.e., the indirect method, k⫽63) using t
statistics gauging the BTAE, dz ⫽t/公(N), mean differences
between self-evaluations and average-evaluations, dz ⫽M
difference
/
SD
difference
, or mean self-evaluations and average-evaluations after
accounting for the pooled standard deviation and bivariate associ-
ation of these measures (Lenhard & Lenhard, 2016;Morris &
DeShon, 2002). When the bivariate association was absent (k⫽
35), we used the mean correlation across 21 studies that provided
this information in order to estimate the missing value (r⫽.34);
sensitivity analyses that utilized a larger (r⫽.47) or smaller
correlation (r⫽.22) to estimate missing values were also con-
ducted (i.e., one standard deviation above or below the mean
correlation). Fourth, we derived a few effect sizes by converting
provided pvalues to tstatistics, which we then converted to dz
(k⫽6).
We calculated separate effect sizes for direct, indirect, percen-
tile, and forced-choice methods. When studies provided effect size
information for multiple attributes, abilities, or traits using the
same method, we averaged these effects to form a single, study-
level estimate. Altogether, we obtained 310 study-level effect sizes
(i.e., 274 studies provided a single effect, 16 studies provided
separate effects for two methods, and one study provided separate
effects for all four methods). The standard error of each effect size,
which was necessary for meta-analytic computations, was 1/公(N)
given that all effect sizes were in standard deviation units (i.e.,
SD ⫽1). We also extracted bivariate correlations of the BTAE
with self-esteem (k⫽14) and life satisfaction (k⫽8) from
relevant studies to evaluate the association of the BTAE with
measures of psychological well-being. We interpreted correlations
as follows: 0.1 ⫽small, 0.3 ⫽medium, 0.5 ⫽large (Cohen,
1988). We selected self-esteem and life satisfaction, because their
association with the BTAE had been examined in several studies;
no other well-being measure had been examined in more than two
studies.
Coding and Extraction of Moderators
The first and second authors coded an initial set of effect sizes
(70%) to enable moderation tests and resolved disagreements by
discussion (all ⬎.86). The remaining effect sizes were coded by
the first author. Specifically, we coded the sample type as college
students or other, and sample culture as East Asian (e.g., people
from China, Japan, and Korea), European American (e.g., people
from Australia, the United Kingdom, and the United States), or
other. In addition, we coded the domain type of comparative
judgments as abilities (e.g., driving ability, mathematics ability,
intelligence), traits (e.g., personality variables, dispositions), or
other (i.e., attributes, or a combination of abilities, attributes, and
traits), and domain valence of comparative judgments as positive
(e.g., happy or intelligent), negative (e.g., unhappy or unintelli-
gent), or both. Next, we coded the scale type utilized to measure
the BTAE as direct, forced-choice, indirect, or percentile. Further,
we coded effects derived from the direct method to determine
whether researchers explicitly labeled the midpoint of the scale as
average (yes or no), and coded studies that used the indirect
method to determine whether the order of self and average other
judgments were counterbalanced (yes or no). Finally, we deter-
mined the specificity of the average other by (a) coding whether
the average other was nonspecific, that is, simply referred to as the
“average person” or “most people” (yes or no), and (b) counting
the number of variables in which the average other was matched to
the participant. As such, we coded studies that referred to a
nonspecific average person as 0, and studies that referred to an
average person of the same age, gender, and race as 3.
We extracted a few additional demographic moderators from
each study. We extracted the percentage of participants who were
female (k⫽235), the percentage of participants in European
American samples who were Caucasian (i.e., White; k⫽36), and
the mean age of participants (k⫽165) from studies that reported
relevant information. Further, some studies provided separate ef-
fect sizes for positive and negative dimensions (k⫽36), or easy
and hard abilities (k⫽7). Although the primary analysis aggre-
gated across all dimensions in a given study, we extracted these
separate effect sizes to enable matched tests of differences in the
BTAE for positive versus negative dimensions and easy versus
hard abilities under equivalent measurement conditions. Similarly,
some studies provided separate estimates of the BTAE for women
and men (k⫽7), European Americans and East Asians (k⫽11),
or European Americans and East Asians on both individualistic
and collectivistic traits (k⫽3). We extracted these separate effects
to enable additional matched tests of gender and cultural differ-
ences in the BTAE under equivalent measurement conditions.
Analytic Strategy
We conducted meta-analytic computations in R, using packages
such as meta and metafor (Schwarzer, Carpenter, & Rücker, 2015;
Viechtbauer, 2010; see also, Harrer, Cuijpers, Furukawa, & Ebert,
2019). We searched for evidence of publication bias in our meta-
analysis using three strategies. First, we examined the distribution
of obtained effect sizes in a funnel plot and used Egger’s test of the
intercept (Egger, Davey Smith, Schneider, & Minder, 1997)to
evaluate whether the distribution was significantly asymmetrical,
as would be expected when publication bias is present. Second, we
used a trim and fill procedure to obtain a bias-corrected estimate of
the overall effect (Duval & Tweedie, 2000). Third, we used selec-
tion model analyses to estimate the overall effect after adjusting
for potential publication bias via weight-function modeling
(Coburn & Vevea, 2019;McShane, Böckenholt, & Hansen, 2016).
We also conducted selection model analyses on key moderator
effects to estimate the influence of publication bias in these con-
ditions.
In addition, we conducted metaregression analyses to evaluate
the association of continuous moderator variables (i.e., % female,
% White, M
age
) with the BTAE. Lastly, we employed a repeated-
measures approach to evaluate potential differences in the BTAE
across positive versus negative dimensions, easy versus hard abil-
ities, and individualistic versus collectivistic traits, with a variance
that accounts for the bivariate association among these judgments
(Borenstein, Hedges, Higgins, & Rothstein, 2009b). Two studies
reported the association among judgments for positive and nega-
tive dimensions (mean r ⫽⫺.01), and no studies reported the
association among judgments for easy versus hard abilities or
individualistic versus collectivistic traits. Based on this limited
information, we entered missing correlations as 0 for these anal-
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126 ZELL, STRICKHOUSER, SEDIKIDES, AND ALICKE
yses. To estimate missing values, we also carried out sensitivity
analyses that utilized a larger (r⫽.30) or smaller correlation
(r⫽⫺0.30).
Results
Overall Effect
Primary model. As expected, the present meta-analysis
yielded strong support for the BTAE. Specifically, there was a
large BTAE after aggregating across 291 independent samples,
dz ⫽0.78, 95% CI [0.71, 0.84] (see Table 1). Nonetheless, there
was considerable variability in the size of the BTAE across sam-
ples, Q⫽71,419.52,
2
⫽0.29, I
2
⫽99.6, which called for
moderation tests exploring the conditions under which it was most
pronounced.
Sensitivity analyses. We conducted follow-up analyses to
explore whether the magnitude of the BTAE was influenced by
assumptions of the primary (i.e., random-effects) model. Along
these lines, a fixed-effect analysis yielded an even larger effect
than the primary model (dz ⫽1.19). However, this outcome likely
reflects the undue influence of five unusually large samples (How-
ell & Ratliff, 2017, Study 1; Kuyper et al., 2011;Mattern et al.,
2010). When these samples were removed, a fixed-effect analysis
yielded an effect size that was very similar to the primary model
(k⫽286, dz ⫽0.78). Further, an unweighted model that simply
took the average of each meta-analytic effect regardless of its
respective sample size (Bonett, 2009;Shuster, 2014) yielded a
nearly identical effect to the primary model (dz ⫽0.78). Lastly, the
magnitude of the BTAE was very similar when missing bivariate
correlations between self and average other judgments (k⫽27)
were estimated to be one standard deviation above (dz ⫽0.78) or
one standard deviation below (dz ⫽0.77) the mean correlation
used in the primary analysis. Taken together, these results suggest
that the BTAE was largely robust to different statistical ap-
proaches.
Publication bias. We used several strategies to evaluate the
degree to which publication bias may have inflated the BTAE.
First, we used Egger’s test of the intercept to evaluate whether
effect sizes were asymmetrical. Although Egger’s test was statis-
tically significant (intercept ⫽⫺4.40, p⬍.001), a bias-corrected
(trim and fill) estimate of effect size was larger than that obtained
in the primary model (dz ⫽1.16, 106 studies added; Figure 3),
rather than smaller as would be expected when publication bias is
present. As a sensitivity analysis, we repeated both publication
bias tests after removing unusually large studies. When the five
studies with unusually large samples were removed, Egger’s test
was not statistically significant (intercept ⫽⫺0.77, p⫽.30) and
a bias-corrected (trim and fill) estimate of effect size was only
slightly larger than that obtained in the primary model (dz ⫽0.87,
29 studies added; Figure 4). In sum, these results are inconsistent
with the presence of publication bias in the effect size distribution
(i.e., selective publication of large or statistically significant ef-
fects).
Next, we quantified the potential effect of publication bias
using selection model analyses. Specifically, we used the
weight-function model to adjust for potential selection bias
(Vevea & Hedges, 1995). When specifying pvalue cutpoints of
0.01, 0.05, and 0.10, there was no significant difference in the
magnitude of the BTAE for the unadjusted model versus the
adjusted model, dz ⫽0.78 versus 0.72,
2
(3) ⫽2.26, p⫽.52.
In addition, we used selection model analyses to estimate the
BTAE assuming varying degrees of selection bias (Vevea &
Woods, 2005). Specific effect size estimates (dz) assuming
different selection biases were as follows: 0.76 moderate two-
tailed, 0.70 moderate one-tailed, 0.73 severe two-tailed, and
0.50 severe one-tailed. Thus, selection model analyses pro-
duced adjusted estimates for the BTAE that were similar to the
unadjusted estimate from our primary model, with the exception
of the severe one-tailed model, where we observed a drop from
0.78 to 0.50. However, although the BTAE dropped in this
model, it remained medium in size despite it being the most
Table 1
Estimates of Overall Effect Size
Estimate type kdz 95% CI
Primary model
Random-effects 291 0.78 [.71, .84]
Sensitivity analyses
Fixed-effect 291 1.19 [1.19, 1.19]
Fixed-effect, dropped huge Nstudies 286 0.78 [.77, .79]
Unweighted 291 0.78 [.71, .84]
Random-effects, dropped huge Nstudies 286 0.77 [.70, .83]
Random-effects, correlation ⫹1SD 291 0.78 [.72, .85]
Random-effects, correlation ⫺1SD 291 0.77 [.71, .84]
Publication bias–corrected estimates
Trim and fill 397 1.16 [1.08, 1.23]
Trim and fill, dropped huge Nstudies 315 0.87 [.80, .93]
Weight function (moderate 2-tail) 291 0.76 —
Weight function (moderate 1-tail) 291 0.70 —
Weight function (severe 2-tail) 291 0.73 —
Weight function (severe 1-tail) 291 0.50 —
Note.N⫽965,307 for the primary model; N⫽45,160 when the five unusually large studies were dropped.
Weight function models do not provide 95% CIs.
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127
BETTER-THAN-AVERAGE EFFECT
stringent test of publication bias. Altogether, the selection
model analyses provide further evidence that publication bias
did not have an undue influence on our estimate of the BTAE
and likely increased it only slightly.
Method type. Next, we compared the size of the BTAE across
the four major methods that have been implemented to assess it
(i.e., direct, indirect, forced-choice, percentile; Table 2). We
placed studies that used multiple methods into a separate category
to maintain independence of observations (k⫽17), and we aver-
aged multiple effects within studies to form a single effect. The
bulk of the studies that we obtained utilized the direct (k⫽120) or
indirect (k⫽102) methods, with far fewer studies utilizing the
percentile (k⫽45) or forced-choice (k⫽7) methods.
An omnibus test yielded significant variability in the magnitude
of the BTAE across methods, Q(4) ⫽14.51, p⫽.006. As
expected, a focused comparison demonstrated that the BTAE was
significantly larger when comparing direct with indirect methods,
dz ⫽0.91 versus 0.70, Q(1) ⫽9.22, p⫽.002. Studies using the
Figure 3. Funnel plot for the trim-and-fill analysis. Dark circles are obtained effect sizes (k⫽291), and light
circles are effect sizes added in the trim-and-fill-analysis (k⫽106).
Figure 4. Funnel plot for the trim-and-fill analysis, after removal of five studies with unusually large samples.
Dark circles are obtained effect sizes (k⫽286), and light circles are effect sizes added via trim-and-fill (k⫽29).
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128 ZELL, STRICKHOUSER, SEDIKIDES, AND ALICKE
forced-choice method yielded the largest effect (dz ⫽1.00), and
studies using the percentile method (dz ⫽0.62) and multiple
methods (dz ⫽0.65) yielded somewhat smaller effects. We ob-
tained an identical pattern of results when we separated effects
from multiple methods into their respective method categories. In
summary, we found a robust BTAE for each of the four methods,
but also found that there was considerable variability in the size of
the BTAE across methods.
Effect size estimates for the major methods used to assess the
BTAE typically remained after assuming different degrees of
selection bias. However, there was a drop in each effect when
examining the most extreme model (i.e., the severe one-tailed
model). Specifically, there was a drop from 0.91 to 0.74 for the
direct method, 1.00 to 0.68 for the forced-choice method, 0.70 to
0.47 for the indirect method, and 0.62 to 0.21 for the percentile
method. These results suggest that publication bias may have
inflated effects for the four major methods, especially the percen-
tile method.
Judgment Domain
Domain type. We observed significant variability in the mag-
nitude of the BTAE across the three domain types, Q(2) ⫽23.59,
p⬍.001 (see Table 3). Consistent with predictions, there was a
significantly larger BTAE among studies that examined trait judg-
ments than ability judgments, dz ⫽0.89 versus 0.51, Q(1) ⫽
23.55, p⬍.001. Studies that examined other domains (e.g.,
attributes or a combination of traits and abilities) yielded a BTAE
that fell in between the other two categories, dz ⫽0.75. Surpris-
ingly, the number of studies examining the BTAE in personality
traits (k⫽164) was more than twice the size of the number of
studies examining abilities (k⫽65).
Effect size estimates for trait and ability judgments typically
remained after assuming different degrees of selection bias. How-
ever, there was once again a drop in effect sizes when examining
the most extreme model (i.e., the severe one-tailed model). In
particular, the BTAE for abilities dropped from 0.51 to 0.09 in this
model. Thus, publication bias may have inflated estimates of the
BTAE in the domain of abilities.
Furthermore, when examining seven matched samples, a within-
subjects approach yielded a significant difference in the magnitude
of the BTAE for easy versus hard abilities, t⫽36.84, p⬍.001 (all
matched samples are listed in Appendix B). This difference re-
mained significant in a sensitivity analysis in which we entered
missing bivariate correlations between abilities as 0.30 or ⫺0.30,
Table 2
Magnitude of the Better-Than-Average-Effect (BTAE) by Method
Method kNdz[95% CI] QTest value Weight function
Independent effects (k⫽289)
Direct 120 838,147 .91 [.81, 1.01] 45,997.3
ⴱⴱ
Q
btw
⫽14.5
ⴱ
.89, .86, .87, .74
Forced-choice 7 1,505 1.00 [.44, 1.57] 674.8
ⴱⴱ
.99, .92, .97, .68
Indirect 102 114,174 .70 [.60, .79] 15,517.4
ⴱⴱ
.68, .63, .65, .47
Multiple 17 7,019 .65 [.33, .97] 1,050.0
ⴱⴱ
.62, .52, .59, .13
Percentile 45 4,462 .62 [.46, .78] 1,090.0
ⴱⴱ
.59, .51, .56, .21
Partially overlapping effects (k⫽310)
Direct 131 843,706 .90 [.83, .96] 49,885.2
ⴱⴱ
—
Forced-choice 9 7,461 .97 [.90, 1.05] 1,308.3
ⴱⴱ
Indirect 116 121,055 .68 [.62, .74] 36,085.6
ⴱⴱ
Percentile 54 10,128 .65 [.57, .72] 1,963.2
ⴱⴱ
Note. Because of a lack of independence, a test value could not be calculated for overlapping effects. Weight function estimates reflect, in order, moderate
two-tail, moderate one-tail, severe two-tail, and severe one-tail selection models.
ⴱ
p⬍.05.
ⴱⴱ
p⬍.001.
Table 3
Magnitude of the Better-Than-Average-Effect (BTAE) by Domain Type
Moderator Group kN dz[95% CI] QTest value Weight function
All effects
Domain type Abilities 65 817,101 .51 [.39, .64] 29,087.4
ⴱⴱ
Q
btw
⫽23.6
ⴱⴱ
.49, .40, .46, .09
Traits 164 119,126 .89 [.80, .98] 16,497.1
ⴱⴱ
.87, .83, .85, .69
Other 62 29,080 .75 [.64, .87] 7,279.9
ⴱⴱ
.74, .71, .72, .63
Domain valence Both 94 14,275 .89 [.80, .98] 2,583.8
ⴱⴱ
Q
btw
⫽8.1
ⴱ
.88, .87, .86, .82
Negative 23 101,677 .83 [.66, 1.01] 3,034.5
ⴱⴱ
.82, .81, .81, .77
Positive 174 849,355 .71 [.62, .80] 53,666.8
ⴱⴱ
.68, .60, .66, .29
Matched comparisons
Ability type Easy 7 373 1.10 [1.06, 1.15] 39.0
ⴱⴱ
t⫽36.8
ⴱⴱ
Hard 7 ⫺.52 [⫺.59, ⫺.46] 88.3
ⴱⴱ
Domain valence Positive 36 2,662 .92 [.86, .98] 570.8
ⴱⴱ
t⫽10.5
ⴱⴱ
Negative 36 .62 [.58, .67] 394.2
ⴱⴱ
Note. Matched comparisons were equivalent in all aspects except the moderating factor. Qvalues are reported for between-subjects comparisons, and t
statistics are reported for within-subjects comparisons. Weight function estimates reflect, in order, moderate two-tail, moderate one-tail, severe two-tail, and
severe one-tail selection models.
ⴱ
p⬍.05.
ⴱⴱ
p⬍.001.
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BETTER-THAN-AVERAGE EFFECT
ts⬎36.25, ps⬍.001. As expected, judgments for easy abilities
yielded a significant BTAE, dz ⫽1.10, but judgments for hard
abilities yielded a significant worse-than-average effect (WTAE),
dz ⫽⫺0.52. Thus, these data suggest that the BTAE is not
inevitable. Alternatively, consistent with an egocentrism account,
people reliably show a WTAE in domains in which they view
themselves unfavorably.
Domain valence. There was significant variability in the mag-
nitude of the BTAE by domain valence, Q(2) ⫽8.07, p⫽.02.
Specifically, the BTAE was significantly smaller when comparing
studies on positive judgment domains to studies on both positive
and negative judgment domains, Q(1) ⫽7.94, p⫽.005, and
nonsignificantly smaller when comparing studies on positive judg-
ment domains to studies on negative judgment domains, Q(1) ⫽
1.53, p⫽.22, with little evidence of publication bias (except a
drop in the severe one-tailed model for positive judgment do-
mains). Nonetheless, this analysis was obscured by the fact that far
more studies examined positive judgment domains (k⫽174) than
both domains (k⫽94) or negative domains (k⫽23), and so it is
possible that these groups of studies systematically varied in other
ways than domain valence.
Addressing this concern, we carried out an unconfounded test of
the effect of domain valence using 36 matched samples (i.e.,
studies that provided separate effect sizes for positive and negative
dimensions under equivalent measurement conditions). A within-
subjects comparison yielded a significant difference, such that the
BTAE was larger for positive dimensions than negative dimen-
sions, dz ⫽0.92 versus 0.62, t⫽10.54, p⬍.001. Further, a
sensitivity analysis showed that the difference between positive
versus negative dimensions remained significant when missing
bivariate correlations between dimensions, which we entered as 0
in the main analysis, were entered as 0.30 or ⫺0.30, ts⬎10.46,
ps⬍.001. In all, although an initial analysis did not yield strong
conclusions regarding the effect of domain valence, data from
matched comparisons provide strong evidence that the BTAE is
elevated on positive versus negative dimensions.
Number of dimensions. Results of a metaregression analysis
yielded a significant positive association between the magnitude of
the BTAE and the number of judgment dimensions included in
each study (p⫽.002; Table 4). These data are consistent with the
argument that people rely on an “I am better-than-average” heu-
ristic when making judgments across many as opposed to few
dimensions.
Sample Characteristics
Culture. Across the entire collection of studies, an omnibus
test yielded no significant difference in the magnitude of the
BTAE when comparing European Americans, East-Asians, and
participants from other cultural groups, Q(2) ⫽1.76, p⫽.42, with
little evidence of publication bias, except for the severe one-tailed
model (see Table 5). Nonetheless, there was a much larger number
of studies on European Americans (k⫽222) than East Asians (k⫽
36) or members of other cultural groups (k⫽33), and, as such, it
is possible that these groups of studies differed in ways besides
culture.
We conducted a more direct comparison of the potential mod-
erating effect of culture by aggregating data from 11 matched
samples, in which European Americans and East Asians were
examined within the same studies. This matched comparison
yielded a statistically significant difference, such that European
Americans evidenced a much larger overall BTAE than East
Asians, dz ⫽0.98 versus 0.40, Q(1) ⫽6.02, p⫽.01.
Furthermore, data from three of these matched samples allowed
us to explore differences in the magnitude of the BTAE across
individualistic and collectivistic traits. Although the BTAE was
significantly larger for European Americans versus East Asians in
the case of individualistic traits, dz ⫽1.20 versus 0.41, Q(1) ⫽
16.01, p⬍.001, there was no significant difference between these
cultural groups in the case of collectivistic traits, dz ⫽0.96 versus
1.03, Q(1) ⫽0.05, p⫽.82. Moreover, although the BTAE did not
significantly differ across individualistic versus collectivistic di-
mensions for European Americans, t⫽1.04, p⫽.32, the BTAE
was significantly smaller on individualistic dimensions for East
Asians, t⫽6.08, p⬍.001. Differences by trait for European
Americans (ts⬍1.03, ps⬎.28) and East Asians (ts⬎6.08, ps⬍
.001) remained unchanged in sensitivity analyses.
Readers should note that these matched analyses are not redun-
dant with the prior meta-analysis on cultural differences in self-
enhancement (Sedikides et al., 2005). Whereas the prior meta-
analysis conceptualized self-enhancement broadly to include both
the BTAE and unrealistic optimism, the present analysis focused
exclusively on the BTAE. In addition, the present analysis in-
cluded data from two articles that were published after the prior
report (Hamamura, Heine, & Takemoto, 2007;Wu, 2018).
Gender. Results from a metaregression analysis produced no
significant association between the magnitude of the BTAE and
the percentage of participants who were female (p⫽.56). We also
addressed the potential influence of gender by focusing on seven
studies that included effect sizes for both gender groups under
equivalent measurement conditions (i.e., each study included an
effect size for men and women derived from the same methods). In
these matched samples, there was no significant difference in the
magnitude of the BTAE for women versus men, dz ⫽0.63 versus
0.61, Q(1) ⫽0.01, p⫽.93, indicating that the BTAE is constant
across gender groups.
Age. As expected, results from a metaregression analysis
yielded a significant association between the mean age of partic-
ipants and the magnitude of the BTAE, such that the effect was
larger in younger as opposed to older samples (p⫽.02). The
youngest sample obtained in this research had a mean age of 5.4
and the oldest sample had a mean age of 70.2. Predicted effect
Table 4
Meta-Regression Analyses Examining Continuous Moderators of
the Better-Than-Average-Effect (BTAE)
Moderator kn B(SE)r
2
# dimensions 291 965,307 .007 (.002)
ⴱ
2.9%
% female 235 154,530 .095 (.162) 0.0%
Age (M) 165 143,482 ⫺.009 (.004)
ⴱ
2.5%
% white 36 11,169 ⫺.509 (.351) 3.1%
Referent specificity 291 965,307 .013 (.028) 0.0%
Note. Values represent regression coefficients (SE).
ⴱ
p⬍.05.
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130 ZELL, STRICKHOUSER, SEDIKIDES, AND ALICKE
sizes (dz) for different age groups are as follows: age 5 ⫽1.01, age
20 ⫽0.88, age 45 ⫽0.66, and age 70 ⫽0.44.
Race. When aggregating across 36 studies that provided rel-
evant information, results from a metaregression analysis yielded
a nonsignificant, negative association between the percentage of
participants who were Caucasian American and the BTAE, p⫽
.16. Thus, when examining European American samples, the
BTAE does not appear to be disproportionately concentrated in
Caucasians versus members of ethnic minority groups.
Sample type. There was no significant difference in the size
of the BTAE when comparing college student samples to other
samples, dz ⫽0.77 versus 0.78, Q(1) ⫽0.05, p⫽.83. Thus, the
BTAE is not limited to college student samples. Further, although
a majority of studies were conducted on college student samples
(k⫽178), over 38% (k⫽113) were conducted on other samples.
The present analysis, therefore, clearly suggests that the BTAE
extends beyond college student convenience samples.
Self-esteem and happiness. There was a medium-sized, pos-
itive association between the BTAE and self-esteem across 14
studies that examined this association, r⫽.34 [CI ⫽.28, .40], n⫽
1,832 (see Appendix C). Similarly, there was a medium-sized,
positive association between the BTAE and overall life satisfaction
across eight studies that examined this association, r⫽.33, 95%
CI [.25, .42], n⫽1,692. As anticipated, therefore, the tendency to
perceive oneself as above average was associated with greater
self-esteem and happiness. However, the moderate size of these
associations indicates that the BTAE is not redundant with self-
esteem and happiness.
Referent Characteristics
Referent specificity. Although it did not reach statistical sig-
nificance, the BTAE was somewhat larger in studies that explicitly
defined the nature of the referent versus studies that did not, dz ⫽
0.81 versus 0.65, Q(1) ⫽2.88, p⫽.09 (see Table 6). There was
little evidence of publication bias for these estimates, except a
notable drop in the severe one-tailed model for studies that did not
explicitly define the referent (i.e., 0.65 to 0.12). However, results
from a metaregression analysis indicated that the magnitude of the
BTAE was not significantly associated with the specificity of the
referent (p⫽.64). Thus, studies that described the average peer in
a highly precise way (e.g., the average person at your school of the
same age and gender) yielded similar BTAEs to studies that
described the average peer in a vague manner (e.g., the average
person).
Table 5
Magnitude of the Better-Than-Average-Effect (BTAE) by Sample Type
Moderator Group kNdz[95% CI] QTest value Weight function
All effects
Sample culture East Asian 36 4,008 .90 [.70, 1.11] 1,996.9
ⴱⴱ
Q
btw
⫽1.8 .88, .83, .86, .63
European American 222 857,997 .76 [.69, .83] 52,497.2
ⴱⴱ
.74, .69, .71, .51
Other 33 103,302 .74 [.54, .95] 5,715.2
ⴱⴱ
.72, .65, .70, .38
Sample type College students 178 820,197 .77 [.68, .86] 29,993.5
ⴱⴱ
Q
btw
⫽.0 .75, .68, .72, .42
Other 113 145,110 .78 [.69, .87] 41,098.6
ⴱⴱ
.77, .74, .75, .63
Matched comparisons
Sample culture East Asian 11 991 .40 [.09, .71] 315.0
ⴱⴱ
Q
btw
⫽6.0
ⴱ
European American 11 686 .98 [.63, 1.33] 207.1
ⴱⴱ
Individualistic traits East Asian 3 136 .41 [.11, .70] 24.1
ⴱ
Q
btw
⫽16.0
ⴱ
European American 3 131 1.20 [.94, 1.45] 14.7
ⴱ
Collectivistic traits East Asian 3 136 1.03 [.71, 1.35] 42.3
ⴱⴱ
Q
btw
⫽.1
European American 3 131 .96 [.41, 1.51] 107.9
ⴱ
Sample gender Men 7 736 .61 [.31, .91] 84.0
ⴱⴱ
Q
btw
⫽.0
Women 7 821 .63 [.38, .88] 78.8
ⴱⴱ
Note. Matched comparisons were equivalent in all aspects except the moderating factor. Weight function estimates reflect, in order, moderate two-tail,
moderate one-tail, severe two-tail, and severe one-tail selection models.
ⴱ
p⬍.05.
ⴱⴱ
p⬍.001.
Table 6
Magnitude of the Better-Than-Average-Effect (BTAE) by Referent Characteristics
Moderator Group kNdz[95% CI] QTest value Weight function
Referent type Not explicit 56 107,567 .65 [.48, .82] 9,696.6
ⴱⴱ
Q
btw
⫽2.9 .62, .52, .60, .12
Explicit 235 857,740 .81 [.74, .87] 53,018.4
ⴱⴱ
.79, .75, .77, .61
Midpoint (direct) Not explicit 63 11,660 .87 [.73, 1.01] 2,796.5
ⴱⴱ
Q
btw
⫽.6
Explicit 57 826,487 .95 [.81, 1.09] 41,299.5
ⴱⴱ
Order (indirect) Balanced 47 5,878 .83 [.70, .96] 814.7
ⴱⴱ
Q
btw
⫽6.8
ⴱ
Other 55 108,296 .59 [.45, .72] 11,168.9
ⴱⴱ
Note. Midpoint type was restricted to direct method studies (k⫽120) and order was restricted to indirect method studies (k⫽102). Weight function
estimates reflect, in order, moderate two-tail, moderate one-tail, severe two-tail, and severe one-tail selection models. Weight function estimates for the
direct and indirect method studies are presented in Table 2.
ⴱ
p⬍.05.
ⴱⴱ
p⬍.001.
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131
BETTER-THAN-AVERAGE EFFECT
Midpoint label. Focusing on the direct method, we found no
significant difference in the magnitude of the BTAE when com-
paring studies that explicitly labeled the scale midpoint average
versus those that did not, dz ⫽0.95 versus 0.87, Q(1) ⫽0.63, p⫽
.43. Therefore, explicitly labeling the midpoint as average does not
appear to influence responses during comparative self-judgment.
Judgment order. Focusing on the indirect method, the BTAE
was significantly larger in studies that counterbalanced self and
average peer-evaluations versus studies that did not, dz ⫽0.83
versus 0.59, Q(1) ⫽6.80, p⫽.009. Of the 55 studies that did not
counterbalance, 23 had participants make self-ratings first, four
had participants make average-ratings first, and 28 did not specify
the order of self and average evaluations.
Discussion
The BTAE is the tendency for people to perceive their abilities,
attributes, and personality traits as superior to those of their aver-
age peer. Prior qualitative reviews of the BTAE literature have
documented its occurrence in various contexts (Alicke & Govorun,
2005;Sedikides & Alicke, 2012), elaborated upon several mech-
anisms that may underlie it (Chambers & Windschitl, 2004;Moore
& Healy, 2008), and highlighted its relevance to self-enhancement
theories (Alicke & Sedikides, 2009;Sedikides & Alicke, 2019).
Going further, the present work provided the first quantitative
review of the BTAE, and in doing so, evaluated several core
questions that have long occupied researchers in this area. Specif-
ically, we synthesized a large body of research on the BTAE,
spanning 124 published articles, 291 independent samples, and
more than 950,000 participants, to evaluate its robustness, as well
as the degree to which it is moderated by sample characteristics
and other methodological features of prior studies.
Our meta-analysis clarified numerous aspects of the BTAE.
First, it demonstrated that the BTAE is highly robust across stud-
ies, with overall effect size estimates that vary from large to very
large, depending upon the statistical approach. The BTAE is larger
than most effects in social-personality psychology, which are
typically small to medium (d⫽0.43; Richard, Bond, & Stokes-
Zoota, 2003). Additionally, with a few exceptions noted below, we
obtained little evidence of publication bias in the BTAE literature,
which lends further confidence in the existence and robustness of
the effect.
Nonetheless, there was substantial variability in the size of the
BTAE across studies. Further, effect size estimates were consid-
erably larger with direct and forced choice methods than with
indirect and percentile methods. On the one hand, these results are
consistent with the argument that cognitive biases such as egocen-
trism and focalism may inflate estimates of the BTAE when direct
measures are used (Chambers & Windschitl, 2004;Moore &
Healy, 2008). On the other hand, it is impressive that a robust
BTAE still remains even when using methods that constrain these
cognitive biases (i.e., the indirect method), and conservative meth-
ods that explicitly define the average as the median rank (i.e., the
percentile method).
Second, our meta-analysis demonstrated variability in the size of
the BTAE across different judgment dimensions. The BTAE was
larger for personality traits than for abilities, likely because per-
sonality traits are more abstract and less subject to external veri-
fication than abilities (Dunning et al., 1989;Van Lange &
Sedikides, 1998). Additionally, when examining 36 matched com-
parisons in which other variables were held constant, the BTAE
was larger for positive dimensions than negative dimensions,
which suggests that the motive to self-enhance (exaggerate one’s
positive qualities) may be more pronounced than the motive to
self-protect (minimize one’s negative qualities). Lastly, consistent
with the argument that the BTAE reflects heuristic processing
(Alicke et al., 2001;Alicke & Govorun, 2005), the effect was
larger when participants rated themselves across many dimensions
rather than few dimensions.
Third, our meta-analysis assessed the degree to which demo-
graphic variables and other methodological factors moderate the
BTAE. An analysis of 11 matched comparisons yielded a signif-
icantly larger BTAE in the case of European Americans than East
Asians. It is possible that the BTAE was larger among European
Americans because the dimensions were of greater cultural impor-
tance to them. Indeed, the three studies that considered dimension
importance found that European Americans exhibited a larger
BTAE on individualistic traits, but there was no difference be-
tween cultural groups on collectivistic traits. Moreover, although
the BTAE varied by culture, it was generally robust in both
European Americans and East Asians, which supports the position
that self-enhancement is universal (Sedikides, 2018;Sedikides et
al., 2015).
Beyond culture, there was little influence of gender or race on
the BTAE. Although the BTAE was slightly larger in younger
samples, it was equally robust in noncollege versus college student
samples. Thus, the disproportionate use of college student conve-
nience samples in this literature does not appear to have inflated
estimates of the effect. Further, the BTAE was larger when exam-
ining indirect method studies that counterbalanced self and aver-
age judgments versus studies that did not do so. Counterbalancing
judgments reflects higher quality methods, and therefore one in-
terpretation of this result is that higher quality studies yield larger
effects. Lastly, the specificity of the referent had a small but
nonsignificant effect on the BTAE. Thus, more work is needed to
understand better the potential moderating effect of referent spec-
ificity on the BTAE.
Fourth, our meta-analysis found that the BTAE was signifi-
cantly and moderately associated with self-esteem and overall life
satisfaction, which is consistent with the argument that self-
enhancement processes correlate with psychological well-being
(Dufner et al., 2019;Taylor & Brown, 1988). Nonetheless, because
self-esteem and life satisfaction are both indicative of personal
adjustment (with self-esteem being merely an indirect measure of
this construct), it remains unclear whether the BTAE is differen-
tially associated with interpersonal adjustment. Although prior
research suggests that self-enhancement processes in general may
not be associated with interpersonal adjustment (Dufner et al.,
2019), the relation of the BTAE specifically with this outcome
could not be tested because of a lack of pertinent studies. More-
over, the correlational nature of our analyses prevents any causal
conclusions regarding the potential impact of the BTAE on psy-
chological adjustment. Future research is needed to examine why
the proclivity for biased self-views evolved despite its potentially
harmful association with interpersonal adjustment. One possibility
is that self-enhancement reaps benefits when expressed in agentic
domains and in early stages of acquaintanceship but reaps costs
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132 ZELL, STRICKHOUSER, SEDIKIDES, AND ALICKE
when expressed in communal domains or in later relationship
stages (Dufner et al., 2019;Sedikides, Hoorens, & Dufner, 2015).
Fifth, we found that the BTAE, both in general and in specific
conditions, largely remained in analyses that accounted for the
possibility of publication bias. Surprisingly, an initial trim and fill
analysis yielded a much larger effect than the primary model (with
over 100 studies added). However, five unusually large samples
had a disproportionate influence on this result, and, because these
studies had large effects (likely owing to a focus on the direct
method or personality traits), many other studies had to be imputed
to create symmetry in the effect size distribution. Indeed, a second
trim and fill analysis that removed the five unusually large samples
yielded a similar result to that of the primary model. Moreover,
selection model analyses typically produced similar effects to that
of the primary model, with the exception to the severe one-tailed
model, where we observed a drop from large to medium for the
overall effect, as well as notable drops for several moderation
effects (e.g., studies on the percentile method, ability judgments,
and positive traits). These results clarify areas of the BTAE liter-
ature in which publication bias may be of elevated concern.
Strengths and Theoretical Implications
This meta-analysis synthesized a large and highly diverse col-
lection of studies, spanning multiple disciplines (e.g., social, per-
sonality, clinical, educational, and applied psychology) to summa-
rize what is currently known about the BTAE. Our work represents
the first appraisal of the overall size and robustness of the BTAE.
Additionally, the use of meta-analysis enabled novel assessments
of potential moderators, including several demographic and meth-
odological moderators that are difficult to measure in primary
empirical studies. Finally, our meta-analytic approach enabled
traditional moderation tests at the between-study level, but also
uniquely enabled aggregation of within-study effects, which iden-
tified pronounced differences in the magnitude of the BTAE as a
function of dimension valence, difficulty, and cultural importance.
A major advantage of this within-study approach is that it isolates
the influence of potential moderating variables, while ensuring that
all other factors are held constant.
More broadly, the meta-analysis contributes to core theories
on self and identity. First, the present findings bolster self-
enhancement theories (Alicke & Sedikides, 2009;Sedikides &
Strube, 1997) by showing that people generally have positively
biased perceptions of their abilities, attributes, and personali-
ties. The BTAE is considered to be a major pillar of self-
enhancement theories (Sedikides & Alicke, 2019), and the highly
robust BTAE identified here indicates that these theories are on
solid footing. Although less direct, the findings are also consistent
with self-verification theory (Swann, 2012), in that selective seek-
ing and exposure to positive feedback may ultimately result in
self-evaluation biases such as the BTAE.
Second, the findings contribute to social comparison theories (Fest-
inger, 1954;Suls & Wheeler, 2017) by showing that comparative
self-evaluations generally reflect self-superiority beliefs. Thus, al-
though people may engage in upward comparisons with superior
others more frequently downward comparisons with inferior others
(Gerber et al., 2018), downward comparisons appear to be more
salient contributors to the self-concept than upward comparisons.
Indeed, one reason why upward comparison may occur more fre-
quently than downward comparison is because people perceive high
status others as more similar to the self than low status others (Collins,
1996). Further, engaging in upward comparisons with similar others
may elevate self-evaluations rather than deflate them (Mussweiler,
2003), given that people may view superior others as an example of
what their future portends rather than a threat to self-superiority
(Lockwood & Kunda, 1997).
Third, the meta-analysis buttresses theoretical perspectives on self-
knowledge, which have long posited gaps and distortions in self-
beliefs (Dunning, 2005;Vazire & Carlson, 2010). The meta-analysis
uniquely advances this literature by estimating the degree to which
people generally have biased perceptions of themselves, and by iden-
tifying conditions under which such biases are most pronounced.
Moreover, the current findings complement prior research on the
accuracy of self-perception. Along these lines, a synthesis of 22
meta-analyses found that self-evaluations of ability are moderately
accurate (Zell & Krizan, 2014), and parallel research has evinced
moderately accurate self-evaluations in the domain of personality
(Vazire & Carlson, 2010). When viewed together with the current
findings, extant research suggests that people have positively biased
views of themselves, while also maintaining reasonably accurate
self-views. Therefore, consistent with a central assertion of the Truth
and Bias Model (West & Kenny, 2011), bias and accuracy in self-
evaluation appear to coexist.
Limitations and Future Directions
Despite these contributions, the meta-analysis also has limitations
and highlights avenues for future research. Only one of the included
articles examined child samples (Hagá, Olson, & Garcia-Marques,
2018), and thus it remains unclear when children begin to show the
BTAE and what developmental processes contribute to its emergence.
Self-verification theory proposes that positive self-beliefs formed in
childhood lead people to later seek feedback and relationship partners
that verify these beliefs (Swann, 2012;Swann & Buhrmester, 2012).
Thus, although research is needed to directly test these assertions in
the context of the BTAE, self-superiority beliefs should emerge early
in life (Thomaes, Brummelman, & Sedikides, 2017) and should
strengthen over time as a function of selective exposure to positive
feedback.
Additionally, most BTAE studies in the meta-analysis involved
European American samples, relatively few studies compared the
magnitude of the effect across cultural groups, and only three studies
compared the effect across cultural groups as a function of the cultural
importance of the self-evaluation dimensions (Heine & Lehman,
1997, Study 1; Hornsey & Jetten, 2005, Study 2; Sedikides et al.,
2003, Study 1). Therefore, more research is needed before strong
conclusions can be made about potential culture by dimension im-
portance interactions in the BTAE. The absence of foreign language
studies was also a key limitation of the meta-analysis that may have
impacted its ability to evaluate cultural differences. Research exam-
ining the non-English literature on the BTAE is in demand. In addi-
tion, future meta-analyses should incorporate unpublished studies on
cultural differences, as studies that fail to find a significant cultural
difference may be less likely to be published.
Besides these demographic considerations, future investigations
will do well to assess the mental health and behavioral correlates of
the BTAE. Although the meta-analysis indicates that the BTAE is
positively associated with personal adjustment (i.e., life satisfaction),
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133
BETTER-THAN-AVERAGE EFFECT
it remains possible that the effect is inversely associated with inter-
personal adjustment (Hoorens, Pandelaere, Oldersma, & Sedikides,
2012;Van Damme, Hoorens, & Sedikides, 2016). Moreover, the
BTAE in health and safety domains may predict adverse outcomes,
such as a failure to engage in necessary precautions (e.g., not wearing
a seatbelt) or excessive risk taking (e.g., driving while intoxicated).
Thus, both the short-term and long-term effects of the BTAE on
consequential, behavioral outcomes await further testing (Chung et
al., 2016).
Lastly, moderation tests in the present meta-analysis were some-
times constrained by insufficient reporting of prior studies. Future
articles should provide detailed demographic information regarding
included samples to facilitate analysis of the effect of age, gender, and
race/ethnicity on the BTAE. Moreover, future articles should report
correlations between self-judgments and average judgments when the
indirect method is used as well as correlations between judgments in
different domains (e.g., positive vs. negative dimensions, hard vs.
easy abilities, individualistic vs. collectivistic traits) when the BTAE
is compared across domains.
Conclusions
The BTAE is widely regarded as both a classic and durable finding
of keen interest to social-personality psychologists as well as behav-
ioral scientists in other specialty areas (Dunning et al., 2004;Kassin
et al., 2017). The present review and meta-analysis provides the most
comprehensive coverage of the BTAE to date. Our work supports the
view that the BTAE is a highly robust and replicable phenomenon.
However, our work also indicates that the BTAE is not inevitable or
impervious to influence. Indeed, the effect varies predictably as a
function of relevant methodological and sample characteristics, and
even reverses under specified boundary conditions. Moreover, al-
though more research is needed, preliminary evidence suggests that
the BTAE is positively associated with psychological well-being. In
short, we hope that our synthesis serves as a one-stop resource for
scholars interested in the BTAE and ultimately inspires research
further exploring the nature and consequences of the effect.
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