Seven reviewers.
One decision letter.
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Upload a manuscript and a panel of specialists reads it in parallel, each looking for something different. You get one prioritized letter, with every issue paired to a concrete fix.
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The manuscript, plus tables and figures as separate files. Nothing is charged yet.
The panel reads in parallel
Up to 7 specialists work at once. You watch each finish and open its report as it lands.
Decision letter
Major against minor revisions, prioritized, each issue paired with a concrete fix.
Statistical Methods
Test selection, assumption violations, power, and interpretation. Returns corrective code in R, Python, or Stata.
- Statistical MethodsReading
- Domain ExpertQueued
- Results AccuracyQueued
- Adversarial SkepticQueued
- Systematic ReviewerQueued
- Pragmatic ReviewerQueued
- Scientific & Technical WriterQueued
- Editor-in-ChiefQueued
What comes back
Not a score and a shrug. Every issue names the location, quotes the passage, and says what to do about it.
Your paired t-test assumes normality. Consider Wilcoxon signed-rank given your sample size of n=12, with corrective R code.
Table 3 reports n=245 but the sum of subgroup ns is 243. This discrepancy should be resolved before submission.
Three recent RCTs directly contradict your stated hypothesis. These should be addressed in your Discussion.
Measured against real peer reviews
This is a preliminary analysis of 5 manuscripts published in The BMJ, not a controlled trial. The complementarity figure cuts both ways: the panel and the journal reviewers each raised substantial issues the other missed. Read the full comparison.
Most papers are not rejected because the research is weak. They are rejected because a methodological, statistical, or analytical problem was not caught early enough.
I am a mathematical statistician and frequent journal reviewer with 70+ publications. PeerGenius puts the work I do as a reviewer in front of you before an editor sees it. More about the project.
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