Editorial Peer Reviewers’ Recommendations at a General
Medical Journal: Are They Reliable and Do Editors Care?
Richard L. Kravitz1*, Peter Franks2, Mitchell D. Feldman3, Martha Gerrity4, Cindy Byrne5, William M.
1Department of Medicine, University of California Davis, Sacramento, California, United States of America, 2Department of Family and Community Medicine, University of
California Davis, Sacramento, California, United States of America, 3Department of Medicine, University of California San Francisco, San Francisco, California, United States
of America, 4Department of Medicine, Oregon Health & Science University Portland, Oregon, United States of America, 5Regenstrief Institute, Indianapolis, Indiana,
United States of America
Background: Editorial peer review is universally used but little studied. We examined the relationship between external
reviewers’ recommendations and the editorial outcome of manuscripts undergoing external peer-review at the Journal of
General Internal Medicine (JGIM).
Methodology/Principal Findings: We examined reviewer recommendations and editors’ decisions at JGIM between 2004
and 2008. For manuscripts undergoing peer review, we calculated chance-corrected agreement among reviewers on
recommendations to reject versus accept or revise. Using mixed effects logistic regression models, we estimated intra-class
correlation coefficients (ICC) at the reviewer and manuscript level. Finally, we examined the probability of rejection in
relation to reviewer agreement and disagreement. The 2264 manuscripts sent for external review during the study period
received 5881 reviews provided by 2916 reviewers; 28% of reviews recommended rejection. Chance corrected agreement
(kappa statistic) on rejection among reviewers was 0.11 (p,.01). In mixed effects models adjusting for study year and
manuscript type, the reviewer-level ICC was 0.23 (95% confidence interval [CI], 0.19–0.29) and the manuscript-level ICC was
0.17 (95% CI, 0.12–0.22). The editors’ overall rejection rate was 48%: 88% when all reviewers for a manuscript agreed on
rejection (7% of manuscripts) and 20% when all reviewers agreed that the manuscript should not be rejected (48% of
Conclusions/Significance: Reviewers at JGIM agreed on recommendations to reject vs. accept/revise at levels barely
beyond chance, yet editors placed considerable weight on reviewers’ recommendations. Efforts are needed to improve the
reliability of the peer-review process while helping editors understand the limitations of reviewers’ recommendations.
Citation: Kravitz RL, Franks P, Feldman MD, Gerrity M, Byrne C, et al. (2010) Editorial Peer Reviewers’ Recommendations at a General Medical Journal: Are They
Reliable and Do Editors Care? PLoS ONE 5(4): e10072. doi:10.1371/journal.pone.0010072
Editor: Margaret Sampson, Children’s Hospital of Eastern Ontario, Canada
Received November 20, 2009; Accepted March 1, 2010; Published April 8, 2010
Copyright: ? 2010 Kravitz et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work was funded, in part, from internal sources made available by the University of California, Davis and Regenstrief Institute. The funders had no
role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: Drs. Kravitz and Feldman are the current editors-in-chief of the Journal of General Internal Medicine. Drs. Tierney and Gerrity are the
immediate past editors-in-chief. Ms. Byrne is managing editor of the journal. This does not alter the authors’ adherence to all the PLoS ONE policies on sharing
data and materials.
* E-mail: email@example.com
Editorial peer review is widely regarded as the cornerstone of
quality assurance in academic medical scholarship.[1,2] Aside from
its broader purpose of fomenting scientific discourse, peer review
serves two instrumental functions: to improve quality of research
reporting (‘‘quality improvement’’) and to aid editors in deciding
whether to accept submitted work (‘‘filtering’’). The Journal of General
Internal Medicine (JGIM) is a peer-reviewed journal focusing on
clinical care, education, and research in general internal medicine
and primary care. Like many of their peers, JGIM editors claim that
‘‘the quality of the papers published in the Journal depends on both
the authors and the external reviewers who help the editors select
the best papers and improve their presentation.’’
We distinguish here between reviewer recommendations (i.e.
accept/revise vs. reject) and reviewer comments (narrative assess-
ment and suggestions for improvement). To the extent that JGIM
editors are influenced in their decisions by reviewer recommen-
dations, ‘‘it is reasonable to expect that experts’ judgment[s] be
somewhat concordant.’’ 
Do peer reviewers assigned the same manuscript tend to issue
similar judgments? Data are conflicting. One early study from the
Journal of Clinical Anesthesia found moderate levels of reviewer
concordance (40% of papers received identical recommendations
from two reviewers and an additional 40% differed by only one
category). However, published data from the fields of
radiology, clinical neuroscience, and rehabilitation sug-
gest that chance-corrected agreement between reviewers is only
fair. Aside from studies of abstracts submitted to scientific
meetings,[9–12] there are to our knowledge only two, relatively
small, studies of the issue in non-specialty journals, conducted in
Croatia and India. In addition, since publication of
PLoS ONE | www.plosone.org1 April 2010 | Volume 5 | Issue 4 | e10072
Siegelman’s classic contribution, few analyses have addressed
the relative contribution of article quality (hypothetically, an
intrinsic property of the manuscript) vs. reviewer style (possibly
ranging from highly skeptical to relatively uncritical) in generating
recommendations to publish or reject. A disproportionate
contribution of reviewer style would raise additional questions
about current mechanisms of peer review.
While perfect agreement among reviewers is arguably unnec-
essary (implying redundancy of effort) or undesirable (perhaps
suggesting excessive cognitive homogeneity in the reviewer pool),
editors should expect reviewer recommendations to be substan-
tially more consistent than mere chance. How much more
consistent? The answer may depend on a particular journal’s
target acceptance rate and decision structure. Hargens suggests
that editors of more selective journals put greater credence in
negative reviews, whereas editors of less selective journals assign
greater weight to positive reviews. These editorial predispositions
may influence who is asked to review, how many reviews are
requested, and how discordant recommendations are recon-
ciled. However, even allowing a healthy degree of variation
in journal policies and practices, it would seem reasonable to
expect that inter-reviewer consistency exceed chance by at least
20% (i.e., kappa .=0.20, commonly viewed as only fair
agreement beyond chance).
We conducted the current study to address three questions.
First, to what extent do peer reviewers at JGIM agree with each
other in their manuscript recommendations? Poor agreement
would suggest that reviewer recommendations (though not their
comments) are not meaningful and should therefore be ignored – or
at least steeply discounted – in making editorial decisions. Second,
to what extent do JGIM editors incorporate reviewer recommen-
dations into their decisions? For example, do they place more
weight on reviewer recommendations than the data warrant?
Finally, to what extent does reviewer style influence recommen-
dations? The results have implications for the editorial process,
and in particular how journal editors should collect, assess, and act
on reviewer recommendations.
Data collection and management
Information on all 6213 manuscripts received by JGIM between
2004 and 2008 (inclusive) were stored in a central database at the
Regenstrief Institute (Indianapolis, Indiana). Each submitted
manuscript underwent two levels of initial internal editorial
screening. First, one of the Co-Editors-in-Chief read the abstract.
Articles felt to be inconsistent with the journal’s mission were
rejected. The remainder were assigned to a Deputy Editor with
expertise relevant to the content of the article. The Deputy Editor
then decided whether to reject the article without external review
or to send the article out for external peer-review. JGIM routinely
sought three peer-reviewers for each manuscript. We analyzed
results for the 2264 manuscripts (36%) that were sent out for
external review. Sources of data included structured forms
completed by peer reviewers (1–4 per manuscript) and final
editorial decisions made by JGIM’s Editors (including Editors-in-
Chief and Deputy Editors)) (1 per manuscript). Neither the Co-
Editors-in-Chief nor Deputy Editors were blinded to the
manuscripts’ authors or institutions. For the first three years of
this study, reviewers were not provided with manuscript authors or
institutions, although no other efforts were made to blind the
reviewers (e.g., removal of references to the authors’ prior
publications). In the fourth year of this study, the authors and
their institutions were provided to the reviewers to give reviewers
the opportunity to comment on possible conflicts of interest.
Data were analyzed using Stata (version 11.0, StataCorp,
College Station, TX). We used kappa statistics to evaluate
chance-corrected agreement among reviewers’ recommendations
to reject vs. accept/revise specific manuscripts. We used mixed
model logistic regression analyses, with individual reviewer
recommendation as the unit of analysis, to adjust reviewers’
recommendations for review year and manuscript type (original
research vs. other). We used random effects models to account for
nesting of reviews by manuscript and by reviewer and to calculate
the intra-cluster correlation coefficients (ICCs) for manuscripts
and reviewers. Because of the cross-nested nature of reviewers
and manuscripts, simultaneous consideration of these variables as
crossed random effects within the same logistic regression using
the entire dataset exceeded the available computing capacity.
Therefore,the reported ICCs
manuscripts and reviewers as the random effect in separate
analyses. The results were consistent with those based on two
other models using a 10% random sample of the data; each
model treated one of the variables as a fixed effect and the other
variable, in turn, as a random effect. We conducted supplemen-
tary analyses to examine possible Deputy Editor effects. (At
JGIM, Deputy Editors have delegated authority to accept or
reject manuscripts.) In these supplementary analyses, the unit of
analysis was the manuscript, the dependent variable was the
Deputy Editor decision (reject vs. not reject), and Deputy Editor
was treated as a random effect.
are based onconsidering
Editorial outcomes of submitted manuscripts
The 2264 manuscripts sent for external review during the study
period received 5881 reviews provided by 2916 reviewers; 3.5%
received one review, 34.6% received two reviews, 60.6% received
three reviews, and 1% received four reviews. (Figure 1). Each
reviewer conducted an average of 2.9 reviews during the study
period (median 2, range 1–14). Among all reviews, 28%
recommended rejection, 28% recommended acceptance (8%
unconditional, 20% conditional), and 45% recommended revi-
sions (15% minor, 26% major, 3% unspecified). Among the 2264
manuscripts, 43% were ultimately accepted, 51% were rejected,
and 6% were withdrawn (Figure 1).
The kappa statistic for inter-reviewer agreement on reject vs.
accept/revise for each manuscript was 0.11 (p,.001); it was 0.14
when there were 4 reviews, 0.12 when there were 3 reviews, and
0.08 when there were 2 reviews. In a mixed effects logistic
regression (taking the reviewer’s recommendation to reject as the
outcome; manuscript type and year of submission as fixed effects;
and manuscript identity as a random effect) the rho coefficient
(ICC) for manuscript identity was 0.17 (95% CI 0.13–0.22),
confirming modest inter-reviewer agreement. The mixed effects
model using reviewer identity as the random effect yielded a
reviewer ICC of 0.23 (95% CI, 0.18 to 0.29, data not shown in
tabular form.) Assuming an ICC of 0.17 (i.e. the manuscript-level
ICC observed in the current study), 7 reviewers would be required
to achieve a Cronbach’s alpha reliability of 0.6 and 18 reviewers
would be needed to yield an alpha of 0.8. With a 50% increase in
the manuscript-level ICC, 4 reviewers would suffice for an alpha of
Peer Reviewer Agreement
PLoS ONE | www.plosone.org2 April 2010 | Volume 5 | Issue 4 | e10072
0.6 and 10 for an alpha of 0.8. With a 100% increase in ICC, the
requisite number of required reviewers would be 2 (for an alpha of
0.6) and 6 (for an alpha of 0.8).
Editorial decision-making in relation to reviewer
Among the 2264 manuscripts reviewed during the study period,
just under half received reviews that were in complete agreement
not to reject (i.e., all reviewers recommended accept/revise), less
than 10% received reviews that were in complete agreement to
reject, and the balance received reviews with conflicting recom-
mendations (Table 1). The editors rejected 48% of 2264
manuscripts sent out for external peer-review. If all reviewers
recommended not to reject, editors rejected the manuscript 20% of
the time. If all reviewers recommended ‘‘reject,’’ editors rejected
88% of the time. And if reviewers were divided, editors rejected
the manuscript 70% of the time (p,.001, Table 1). There was no
significant relationship between the number of reviews and the
initial editorial decision to reject (chi-square=1.9, degrees of
Deputy editor effects
The 57 Deputy Editors managed 2–179 manuscripts (mean
102). In an analysis using manuscript as the unit of analysis and the
assigned Deputy Editor as a random effect, taking initial editorial
decision (reject or not) as the dependent variable, and no
independent variables, the Deputy Editor ICC was 0.02 (95%
CI, 0.01 to 0.06). When this model adjusted also for reviewer
agreement (complete agreement to reject, complete agreement to
accept, or disagreement), manuscript year and article type, the
Deputy Editor ICC increased to 0.03 (95% CI, 0.02 to 0.08).
The results of this analysis suggest that reviewers for JGIM
agreed on the disposition of manuscripts at a rate barely
exceeding what would be expected by chance. Nevertheless,
JGIM editor’s decisions appeared to be significantly influenced by
reviewer recommendations. In particular, agreement by all
reviewers that a manuscript should be rejected (an uncommon
occurrence in our data) essentially sealed its fate. Consensus
among reviewers that a manuscript deserved further consider-
ation (either an opportunity to revise and resubmit or conditional
acceptance) reduced the likelihood of rejection from approxi-
mately half (for all manuscripts sent out for peer-review) to about
one in five. These results challenge biomedical journal editors to
reconsider what is now standard practice: asking reviewers to
provide recommendations to accept, revise, or reject submitted
Of the two instrumental purposes served by peer review
(quality improvement, and decision making or ‘‘filtering’’),
filtering is arguably less important to the biomedical enterprise
as a whole, since most rejected manuscripts eventually get
published. [18,19] In addition, some journals have explicitly
rejected the filtering function, promising to publish all manu-
scripts within the journal’s scope that are ‘‘technically sound’’
time being, however, placement of a manuscript within a
particular journal is of great significance to readers, authors,
and authors’ institutions. Busy clinician-readers fix their attention
on a limited number of journals, chosen according to the
journals’ clinical focus and impact.[20,21] Authors expend
considerable energy preparing articles for specific journals,
slanting their presentation to meet the needs and expectations
Figure 1. Flow chart showing outcome of reviews pertaining to
2264 manuscripts undergoing external peer review at the
Journal of General Internal Medicine.
Table 1. Likelihood of Initial Decision to Reject in Relation to Reviewer Agreement.
Reviewer RecommendationsN (%)Fraction Rejected by Editors (%)
Complete agreement not to reject 1080 (47.7)20.3
Any level of disagreement1027 (45.4)70.6
Complete agreement to reject157 (6.9)88.5
Total 2264 (100)47.8
Peer Reviewer Agreement
PLoS ONE | www.plosone.org3 April 2010 | Volume 5 | Issue 4 | e10072
of particular readerships. Academic institutions use publication
venue as a factor in making tenure and promotion decisions.
As long as journals are complicit in this process, they have a duty
to assess and improve the processes they use to accept or reject
articles for publication.
In this light, the results of this study are provocative. Reliability
is a pre-requisite for validity, and the reliability of reviewer
recommendations at JGIM (and possibly at other journals) is low.
Peer review serves multiple purposes, including social functions
such as managing the process by which a ‘‘community certifies
additions to its body of accepted knowledge’’. In addition,
editors may put reviewers’ recommendations to some less-than-
obvious purposes. For example, some editors may use the
recommendations ‘‘check box’’ to calibrate reviewers’ narrative
comments, especially those visible to authors. Nevertheless, we are
unpersuaded that because ‘‘reviewers advise and editors decide,’’
inter-reviewer reliability is moot. Like JGIM, most biomedical
journals routinely ask reviewers for summative advice about
priority for publication. If reviewers cannot regularly agree on
whether to recommend rejection or further consideration, the
marginal contribution of such summative recommendations may
be small, and worse, they may distract from reviewers’ primary
contribution, which is to improve the reporting – and ultimately
the performance – of science.
Several solutions might be entertained. First, editors might
solicit more reviewers per manuscript; however, given ICCs in the
range reported here, it would take 18 reviews per manuscript to
push the coefficient alpha above 0.8. Given the difficulty
JGIM and other journals are having securing peer-reviews,
such a recommendation is impractical. However, it might be
applicable to post-publication review, using an approach like that
of the McMaster Online Rating of Evidence program.
A second solution is to improve the process of peer review by
providing more effective guidance to reviewers or by working to
enhance the psychometric properties of the questions that are
posed to them. JGIM hosts an annual peer review workshop at a
national meeting but (for obvious reasons) does not require
attendance. JGIM also provides guidelines for reviewers on its
website (http://jgim.iusm.iu.edu/) but does not monitor website
traffic nor formally certify reviewer competence. More formal
attempts at reviewer training have met with mixed results.
With regard to measurement, most journals ask reviewers to rate
different dimensions of manuscript quality on makeshift Likert
scales. However, the reliability and validity of these scales and
their relation to reviewer recommendations require further
Finally, journal editors could consider a break with tradition by
dispensing with reviewer recommendations altogether, asking
them to focus instead on evaluating the strengths and weaknesses
of manuscripts across multiple dimensions and particularly on
suggestions for improvement. Under this approach, the role of the
reviewer would be realigned to emphasize evaluation and
constructive criticism rather than decision-making. Again, such
an approach should undergo a formal evaluation.
It is interesting to note that recommendations were more
consistent for multiple manuscripts assigned to the same reviewer
(intra-class correlation coefficient rho=0.23) than for multiple
reviewers assessing the same manuscript (rho=0.17). These results
provide evidence that reviewers have an evaluation style that
exerts itself across manuscripts. Any college undergraduate knows
that there are hard and easy graders among professors, but it is still
surprising that the propensity of reviewers to be generous or tough
is quantitatively larger than the tendency of different raters to
recommend rejection (vs. further consideration) of the same
manuscript. In a study conducted at the American Journal of
Radiology, Siegelman identified 8 ‘‘zealots’’ (very easy graders)
and 9 ‘‘assassins’’ (very hard ones) among 660 reviewers who had
reviewed at least 10 manuscripts. Our data indicate that inter-
reviewer variability is much more pervasive; it is not just outliers
who adopt a particular ‘‘style.’’ The existence of such a style effect
and its potential arbitrary influence on the fate of manuscripts
also raises questions about the probative value of reviewer
In contrast to the evidence for a modest reviewer style effect,
there was little evidence for a substantive Deputy Editor style
effect on initial rejection decisions. While the Deputy Editor
rho was statistically significant, it was small (0.02) and increased
only to 0.03 after adjusting for the effect of reviewer agreement,
manuscript year and article type. It remains possible that
editors exert a style effect through their selection of specific
This report has certain limitations. Most importantly, the data
were obtained from a single general medical journal, and
generalizability is therefore limited. However, manuscripts
submitted to JGIM encompass a wide array of topics including
clinical and health services research, clinical medicine, medical
education, and health policy, so these findings may be relevant to
a wide array of general medical journals. Moreover, many JGIM
reviewers are academic general internists with extensive training
in clinical epidemiology, health services research, critical
appraisal, and biostatistics. Concordance within this methodo-
logically minded cohort of reviewers might be expected to be, if
anything, higher than for the average clinical journal. Other
limitations include the relatively short evaluation period, likely
non-random assignment of manuscripts to reviewers (editors may
choose ‘‘hard graders’’ to review papers they don’t like), and lack
of data on outcomes (e.g., citation counts for articles published
with reviewer concordance vs. those published despite reviewer
disagreement). Further, we did not investigate the informational
content of reviewers’ narrative comments nor their impact on
editorial decision-making. It remains possible that such com-
ments drive editorial decisions in a more reliable and valid
fashion than reviewers’ summary recommendations. Finally,
there is no guarantee that any of the potential solutions discussed
here will work better than the current system. A Cochrane
review concluded there is scant evidence to support the current
process of editorial peer review. Further study, including
randomized controlled trials, is needed before implementing
changes to a system that has withstood the test of time, if not
In summary, reviewer publication recommendations over a five-
year period at the Journal of General Internal Medicine showed scant
agreement but were nonetheless accorded considerable weight by
the editors. Reviewers appear to have a relatively stable style that
influences their recommendations over time and across manu-
scripts. Biomedical journal editors should look carefully at their
own data – and pool data across journals – in an effort to create a
more reliable and valid review process.
Conceived and designed the experiments: RLK PF MDF WT. Performed
the experiments: MG CB WT. Analyzed the data: PF. Wrote the paper:
RLK PF MDF MG WT. Made substantive contributions to the
manuscript: PF. Contributed to drafts of the manuscript: MDF MG.
Maintained the editorial database: CB. Reviewed the final manuscript: CB.
Edited the manuscript: WT. Made substantive contributions to the final
Peer Reviewer Agreement
PLoS ONE | www.plosone.org4 April 2010 | Volume 5 | Issue 4 | e10072
1. Relman AS (1990) Peer review in scientific journals–what good is it? West J Med
2. Goodman SN, Berlin J, Fletcher SW, Fletcher RH (1994) Manuscript quality
before and after peer review and editing at Annals of Internal Medicine. Ann
Intern Med 121(1): 11–21.
3. Tierney W, Gerrity M (2008) Thanks to Reviewers. J Gen Intern Med 23(12):
4. Hojat M, Gonnella JS, Caelleigh AS (2003) Impartial judgment by the
‘‘gatekeepers’’ of science: fallibility and accountability in the peer review process.
Adv Health Sci Educ Theory Pract 8(1): 75–96.
5. Cullen DJ, Macaulay A (1992) Consistency between peer reviewers for a clinical
specialty journal. Acad Med 67(12): 856–9.
6. Howard L, Wilkinson G (1998) Peer review and editorial decision-making.
Br J Psychiatry 173: 110–3; discussion 4-5.
7. Rothwell PM, Martyn CN (2000) Reproducibility of peer review in clinical
neuroscience. Is agreement between reviewers any greater than would be
expected by chance alone? Brain 123 (Pt9): 1964–9.
8. Wade D, Tennant A (2004) An audit of the editorial process and peer review in
the journal Clinical rehabilitation. Clin Rehabil 18(2): 117–24.
9. Kemper KJ, McCarthy PL, Cicchetti DV (1996) Improving participation and
interrater agreement in scoring Ambulatory Pediatric Association abstracts. How
well have we succeeded? Arch Pediatr Adolesc Med 150(4): 380–3.
10. Montgomery AA, Graham A, Evans PH, Fahey T (2002) Inter-rater agreement
in the scoring of abstracts submitted to a primary care research conference.
BMC Health Serv Res 2(1): 8.
11. Rubin HR, Redelmeier DA, Wu AW, Steinberg EP (1993) How reliable is peer
review of scientific abstracts? Looking back at the 1991 Annual Meeting of the
Society of General Internal Medicine. J Gen Intern Med 8(5): 255–8.
12. Montgomery AA, Graham A, Evans PH, Fahey T (2002) Inter-rater agreement
in the scoring of abstracts submitted to a primary care research conference.
BMC Health Serv Res. [Article] 2: 4.
13. Marusic A, Mestrovic T, Petrovecki M, Marusic M (1998) Peer review in the
Croatian Medical Journal from 1992 to 1996. Croat Med J 39(1): 3–9.
14. Gupta P, Kaur G, Sharma B, Shah D, Choudhury P (2006) What is submitted
and what gets accepted in Indian Pediatrics: analysis of submissions, review
process, decision making, and criteria for rejection. Indian Pediatr 43(6): 479–89.
15. Siegelman SS (1991) Assassins and zealots: variations in peer review. Special
report Radiology 178(3): 637–42.
16. Hargens LL (1988) Scholarly Consensus and Journal Rejection Rates. American
Sociological Review 53(February): 139–51.
17. Viera AJ, Garrett JM (2005) Understanding interobserver agreement: the kappa
statistic. Fam Med 37(5): 360–3.
18. Hall SA, Wilcox AJ (2007) The fate of epidemiologic manuscripts: a study of
papers submitted to epidemiology. Epidemiology 18(2): 262–5.
19. Liesegang TJ, Shaikh M, Crook JE (2007) The outcome of manuscripts
submitted to the American Journal of Ophthalmology between 2002 and 2003.
Am J Ophthalmol 143(4): 551–60.
20. Haynes RB, McKibbon KA, Fitzgerald D, Guyatt GH, Walker CJ, et al. (1986)
How to keep up with the medical literature: II. Deciding which journals to read
regularly. Ann Intern Med 105(2): 309–12.
21. Laine C, Weinberg DS (1999) How can physicians keep up-to-date? Annu Rev
Med 50: 99–110.
22. Grzybowski A (2009) The journal impact factor: how to interpret its true value
and importance. Med Sci Monit 15(2): SR1–4.
23. Tierney W, Gerrity M, Byrne C (2009) Five years before the masthead: Our
journey with the Journal of General Internal Medicine. J Gen Intern Med In
24. Haynes RB, Cotoi C, Holland J, Walters L, Wilczynski N, Jedraszewski D, et al.
(2006) Second-order peer review of the medical literature for clinical
practitioners. JAMA 295(15): 1801–8.
25. Schroter S, Tite L, Hutchings A, Black N (2006) Differences in review quality
and recommendations for publication between peer reviewers suggested by
authors or by editors. JAMA 295(3): 314–7.
26. Strayhorn J, Jr., McDermott JF, Jr., Tanguay P (1993) An intervention to
improve the reliability of manuscript reviews for the Journal of the American
Academy of Child and Adolescent Psychiatry. Am J Psychiatry 150(6): 947–52.
27. Jefferson T, Rudin M, Brodney Folse S, Davidoff F (2007) Editorial peer review
for improving the quality of reports of biomedical studies. Cochrane Database
Syst Rev (2): MR000016.
Peer Reviewer Agreement
PLoS ONE | www.plosone.org5 April 2010 | Volume 5 | Issue 4 | e10072