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Comparing apples and oranges: A randomised prospective study

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James Barone
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For many years the comparison of apples and oranges was thought to be impossible. Many authors use the analogy of the putative inability to compare apples and oranges as a means of scornfully reviewing the work of others. The titles of some recent publications 1 2 suggest an actual comparison of apples and oranges, but the authors do not, in fact, compare these two fruits. Our laboratory has been interested in this problem for many years. We attempted numerous pilot studies (unpublished data) but had not accomplished a true comparison until now. At last, successful comparison of apples and oranges has been achieved and is the subject of this report. We investigated …
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Compar ing apples and oranges: a randomised
prospective study
James E Barone
For many years the comparison of apples and oranges
was thought to be impossible. Many authors use the
analogy of the putative inability to compare apples and
oranges as a means of scornfully reviewing the work of
others. The titles of some recent publications
12
suggest
an actual comparison of apples and oranges, but the
authors do not, in fact, compare these two fruits. Our
laboratory has been interested in this problem for
many years. We attempted numerous pilot studies
(unpublished data) but had not accomplished a true
comparison until now. At last, successful comparison of
apples and oranges has been achieved and is the
subject of this report.
Methods and results
We investigated many different varieties of apples and
oranges in pilot studies; for this study, however, red
delicious apples were compared with navel oranges.
A total of 12 objects (6 apples, 6 oranges) made up
the experimental population. Measurements were
performed using a standard tape measure (Pseudo-
scientific Instruments, Lodi, NJ). Weight was recorded
to the nearest tenth of a gram using a scale. Sweetness
was quantified by the Licker scale (1 = kind of sweet;
2 = sweet; 3 = very sweet; 4 = really very sweet). Statisti-
cal calculations were performed using FudgeStat
(Hypercrunch Corporation, Sunnyvale, CA) on an
Apple Macintosh 8500 computer (Apple Computer
Inc, Cupertino, CA). No significance should be
inferred from the type of computer used, nor was
any bias introduced because of this. Six oranges
and five apples survived the experiment. (Before the
study was completed, the author’s 12 year old son,
Thomas, inadvertently consumed one of the objects,
an apple.) Non-parametric background comparisons
are shown in table 1. A striking and heretofore
unappreciated similarity was noted. In only one
category, that of “involvement of Johnny Appleseed,”
was a statistically significant difference between the
two fruits found.
Subjective findings and objective data are pre-
sented in table 2. A significant difference between
apples and oranges was identified only in the
categories of colour and seeds.
Comment
The study reported herein represents a breakthrough
in the comparison of apples and oranges. These two
fruits appear to have many features in common, as we
noted differences in only three of 15 areas.
A Medline search found 52 publications unrelated
to the actual study of fruit with the words “apples” and
“oranges” in their titles; most are letters to the editor or
editorials. Articles in the medical literature on the sub-
ject of apples and oranges are increasingly being pub-
lished (see figure). Every one of these studies asserts
Table 1 Non-parametric background fructological information
Apples Oranges
Grown in orchards Yes Yes
Flowering trees Yes Yes
Considered a fruit Yes Yes
May be eaten Yes Yes
May be made into juice Yes Yes
Subject to damage by disease Yes Yes
Subject to damage by insects Yes Yes
Involvement of Johnny Appleseed* Yes No
*P<0.01.
Table 2 Subjective and objective comparison of apples and
oranges
Apples Oranges P value
Colour Red Orange 0.03
Sweetness 2+ 2+ NS
Shape Sphere Sphere NS
Mean (SD) circumference (cm) 25.6 (2.3) 24.4 (2.6) NS
Mean (SD) diameter (cm) 7.9 (0.6) 7.6 (0.7) NS
Weight (gm) 340 (87) 357 (760) NS
Seeds Yes No 0.03
Table 3 Actual subjects of selected papers purported to be comparisons of apples and
oranges
Title of paper Actual subject
Comparing apples with oranges
1
Generalists and specialists
Comparing apples to oranges
2
Desflurane and propofol
Apples and oranges
3
Emergency medical systems
Apples and oranges: flaws and guffaws
4
Salmeterol and ipratroprium
Comparing apples and oranges in the Plio-Pleistocene: methodological
comments on meat-eating by early hominids at the FLK 22 Zinjanthropus site,
Olduvai Gorge (Tanzania): an experimental approach using cut-mark data
5
Self explanatory
10
8
6
4
2
0
1971 75 80 85 90 95 99
Year
No of papers
r
2
= 0.2081
Incidence of “apples and oranges” in the medical literature
Practice and research
Stamford Hospital,
Stamford, CT
06904, USA
James E Barone
surgeon in chief
drjbarone@
stamhosp.chime.org
BMJ 2000;321:1569–70
1569BMJ VOLUME 321 23–30 DECEMBER 2000 bmj.com
that a comparison of apples and oranges is impossible.
At first glance, some papers seemed to have
addressedthe important topic of a real comparison of
apples and oranges. Table 3 reveals the truth.
This article, certain to become the classic in the field,
clearly demonstrates that apples and oranges are not
only comparable; indeed they are quite similar. The
admonition “Let’s not compare apples with oranges”
should be replaced immediately with a more appropri-
ate expression such as “Let’s not compare walnuts with
elephants” or “Let’s not compare tumour necrosis factor
with linguini.”
This paper was presented in part as the presidential address
at the Connecticut Society of American Board Surgeons,
December 1998.
Funding: None.
Competing interests: None declared.
1 Johnson W. Comparing apples with oranges. Arch Intern Med 1998;158:
1591-2.
2 Lubarsky DA. Comparing apples to oranges. Anesth Analg 1995
Aug;8:428-9.
3 Cummins RO, Hazinski MF. Apples and oranges. Ann Emerg Med
1999;33:602-3.
4 Petty TL. Apples and oranges: flaws and guffaws. Chest 1999;116:1137-8.
5 Monahan CM. Comparing apples and oranges in the Plio-Pleistocene:
methodological comments on meat-eating by early hominids at the FLK
22 Zinjanthropus site, Olduvai Gorge (Tanzania): an experimental
approach using cut-mark data. J Hum Evol 1999;37:789-92.
How not to give a presentation
Richard Smith
T
he invitation arrives. You are invited to speak
on the same programme as the Pope, Bill Clin-
ton, and Madonna. Beside yourself with excite-
ment, you forget that you’ve had these sort of
invitations before
—
and that, for some strange reason,
none of the famous people ever turn up. They are all
replaced by people you’ve never heard of and who turn
out to be even more boring than you. Having accepted
the invitation, you get your own back by forgetting it
completely. Two years later, 15 minutes before you are
due to start speaking in Florence, you receive a
telephone call in your office in London asking where
you are.
“I’m sorry,” you answer lamely, “I forgot.”
“Don’t worry,” answers the cheery voice at the end,
“We’ll just ask Madonna to speak for 20 minutes
longer. The audience of world leaders will be
disappointed you’re not here, but extra Madonna will
be some compensation.”
Far from ruining this presentation, you may have
improved the world leaders’ conference. But forgetting
altogether that you agreed to speak is a good way to
make a mess of your presentation. A variant is to arrive
late. Don’t arrive too late because they will simply have
cancelled your session, probably sending a thrill of
pleasure through an audience facing the prospect of
five consecutive speakers.
Preparing for a bad presentation
One way to prepare for a bad presentation is not to
prepare at all. Step up to the platform, open your
mouth, and see what comes out. With luck, your talk
will be an incoherent ramble. This is, however, a high
risk strategy because spontaneity may catch you out.
Most medical presentations are so premeditated that
spontaneity may inspire both your audience and you.
Inspiration must be avoided at all costs. Similarly you
might be caught out by truth: “I’ve been asked to pro-
mote this new drug, but actually I’d be fearful of throw-
ing it into the Thames because it might poison the few
shrivelled fish that survive there.” Truth is compelling
to an audience, even if mumbled.
A really bad presentation needs careful preparation.
A useful standby is to prepare for the wrong audience. If
asked to speak to Italians speak in German. If the audi-
ence is composed of 15 year olds then prepare a
complex talk that would baffle a collection of Nobel
prize winners. It’s much the best strategy to give an over-
complicated presentation. “Nobody ever lost money
underestimating the public’s intelligence,” said Barnum,
Richard Nixon, or somebody, and so you may be
surprised by how well your grossly oversimplified
presentation is received by your audience of professors.
Be sure to prepare a presentation that is the wrong
length. Too long is much the best. Most of the audience
will be delighted if your talk is too short, not least
because it may provide more opportunity for them to
hear their own voices. But something that is too long
always depresses an audience, even if what you are say-
ing is full of wit and wisdom.
Another trick is to ignore the topic you are given.
Simply give the bad presentation that you have honed
to the point of perfection by deleting anything that
raises a flicker of interest. With luck, most of the audi-
ence will have heard it several times before.
You may be able to enhance your bad presentation
by sending the organisers in advance a long and dull
curriculum vitae. Your presentation may then be pref-
aced by the chairman reading out your whole boring
life story in a monotone. If you are lucky you might find
yourself beginning your presentation after you were
supposed to finish.
Practice and research
BMJ, London
WC1H 9RJ
Richard Smith
editor
BMJ 2000;321:1570–1
1570 BMJ VOLUME 321 23–30 DECEMBER 2000 bmj.com
... Because the genome and the environome are fundamentally different entities, one might say that we are comparing apples with oranges. Yet apples and oranges are both fruit that are sweet; are similar in size, weight, and shape; are grown in orchards; and may be eaten, juiced, and baked (Barone, 2000). We argue here that genetic and environmental influences on people's differences in affect, behavior, and cognition are similar enough to apply insights from one research domain to the study of the other. ...
From Genome-Wide to Environment-Wide: Capturing the Environome
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Genome-wide association (GWA) studies have shown that genetic influences on individual differences in affect, behavior, and cognition are driven by thousands of DNA variants, each with very small effect sizes. Here, we propose taking inspiration from GWA studies for understanding and modeling the influence of the environment on complex phenotypes. We argue that the availability of DNA microarrays in genetic research is comparable with the advent of digital technologies in psychological science that enable collecting rich, naturalistic observations in real time of the environome, akin to the genome. These data can capture many thousand environmental elements, which we speculate each influence individual differences in affect, behavior, and cognition with very small effect sizes, akin to findings from GWA studies about DNA variants. We outline how the principles and mechanisms of genetic influences on psychological traits can be applied to improve the understanding and models of the environome.
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... Researchers' attempts to improve how to compare simulated data with observational data are to be commended, but they should be careful about using overconfident language and giving the impression that near-perfect comparisons of data between model and observations is possible and are necessary (Cowtan et al., 2015;Tokarska et al., 2019;Lewandowsky et al., 2019). In this study, I hope to have shown that a theoretical "apples-to-apples" approach (Hawkins, 2015) is not necessarily superior to standard approaches, as "apples and oranges are not only comparable; indeed they are quite similar" (Barone, 2000). ...
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Simulated historic near‐surface air temperature variations are often compared with observations of land air temperatures blended with sea surface temperatures. This study investigates claims that this is not a “true like‐with‐like” comparison, which may cause small biases in simulated twentieth century temperature changes, with implications for different climate attribution and projection studies. A more appropriate analysis, it is claimed, should use simulated sea surface temperatures blended with land air temperatures; an apparent discrepancy with observed trends is then reduced. As the temperature of the uppermost level in a model's ocean is used to represent simulated sea surface temperatures, that models have inconsistent ways of representing land, and that simulations have differing sea ice coverages, the claim of an idealised analysis approach is challenged. An examination of Coupled Model Intercomparison Project simulations, compared with an observational dataset of near‐surface temperatures, suggests there is a bias in simulated historic trends when upper‐ocean temperatures are used instead of marine air temperatures, but this bias is small compared to other model and observational uncertainties and the impact of analysis choices. The results indicate that it is generally appropriate to use global near‐surface air temperature diagnostics to compare simulated historic climate change with observed temperature changes. Alternative model diagnostics are not necessarily superior to those used in standard approaches, and the emphasis of model and observational discrepancies may be based on overconfident reasoning.
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... Thus, we can break down the apple versus orange decision into smaller parts (elements) as fully objective comparisons, subjective comparisons, and some that might be termed quasiobjective, in that they can rely on third party or expert opinion being nonpartisan and at least derived, in part, from a desire to be data-driven. Example studies comparing apples and oranges have been published by both NASA [6] and in the BMJ [7]. ...
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... Despite the strengths of the proposed review, however, the wide range of interventions and target problems that are likely to be addressed by the primary research studies may lead to a relatively heterogeneous group of studies (and thus, potentially effect sizes) which may lead to concerns that we are not comparing 'like with like' (cf. the problem of mixing apples and oranges 70 ) and limit the extent to which the findings can be generalised to a specific population (eg, to those with depression). However, to mitigate these concerns we will use moderation analysis to investigate specific factors that might influence the effect of improvements in sleep on mental health and to estimate the sample-weighted average effect sizes for different types of interventions and on different mental health outcomes. ...
Does improving sleep lead to better mental health? A protocol for a meta-analytic review of randomised controlled trials
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Introduction Sleep and mental health go hand-in-hand, with many, if not all, mental health problems being associated with problems sleeping. Although sleep has been traditionally conceptualised as a secondary consequence of mental health problems, contemporary views prescribe a more influential, causal role of sleep in the formation and maintenance of mental health problems. One way to evaluate this assertion is to examine the extent to which interventions that improve sleep also improve mental health. Method and analysis Randomised controlled trials (RCTs) describing the effects of interventions designed to improve sleep on mental health will be identified via a systematic search of four bibliographic databases (in addition to a search for unpublished literature). Hedges’ g and associated 95% CIs will be computed from means and SDs where possible. Following this, meta-analysis will be used to synthesise the effect sizes from the primary studies and investigate the impact of variables that could potentially moderate the effects. The Jadad scale for reporting RCTs will be used to assess study quality and publication bias will be assessed via visual inspection of a funnel plot and Egger’s test alongside Orwin’s fail-safe n. Finally, mediation analysis will be used to investigate the extent to which changes in outcomes relating to mental health can be attributed to changes in sleep quality. Ethics and dissemination This study requires no ethical approval. The findings will be submitted for publication in a peer-reviewed journal and promoted to relevant stakeholders. PROSPERO registration number CRD42017055450.
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... Authors of 25 of the meta-analyses could have chosen their criteria after the selection was made. Finally, in 19 of the reviews, the outcome measures were not identical from one study to another; the review was comparing apples with oranges [65]. All the metaanalyses published in the Journal of the American Medical Association, in the period 2005 to 2006 were flawed, as summarised in Table 1. ...
The failure of evidence-based medicine?
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... The title phrase "comparing chalk with cheese," as suggested by an anonymous reviewer, was chosen over "comparing apples with oranges," because apples and oranges can actually be compared quite well. 42,43 ...
Comparing Chalk With Cheese—The EGG Contact Quotient Is Only a Limited Surrogate of the Closed Quotient
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Reconciling Apples & Oranges: A Constructivist SoTL Writing Program
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Faculty new to SoTL, especially when they consider writing for publication, often react by focusing on how different it is—apples and oranges—from their familiar disciplinary processes and products. Although there are indeed significant differences between individual disciplines and SoTL, appealing to the similarities can demystify SoTL as disciplinary experts reach out of their comfort zones and into areas of research and writing that often make them doubt themselves. We fill a gap in the SoTL literature by describing how to go from data analysis to publication in SoTL. We also report on our descriptive study delving into the complexities of participants’ experiences, helping us come to a greater understanding of how to support this work.
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Comparing Apples With Oranges
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Comparing apples and oranges in the Plio-Pleistocene: Methodological comments on "Meat-eating by early hominids at the FLK 22 Zinjanthropus site, Olduvai Gorge (Tanzania): An experimental approach using cut-mark data"
Article
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L'auteur presente la critique de l'article Meat-eating by early hominids at the FLK 22 Zinjanthropus site, Olduvai Gorge (Tanzania) : an experimental approach using cut-mark data ecrit par Monsieur Dominguez-Rodrigo en 1997.
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