Pre-Analysis Plan Peer Review Assessment
A structured instrument for expert reviewers to evaluate the clarity, completeness, and pre-specification quality of a pre-analysis plan or preregistration draft before data collection begins.
Sample questions
A preview of what’s in the template. Every question is editable before you launch.
Which materials did you review for this assessment? Select all that apply.
- Research question brief
- Full PAP/preregistration draft
- Hypotheses section
- Outcome definitions
- Analysis plan
- Power analysis
- Data dictionary / variable list
- Inclusion/exclusion rules
- Mock tables/figures
- Other
Each hypothesis is clearly labeled (e.g., H1, H2) and easy to identify.
The primary outcome is operationally defined (i.e., exact variable, measurement method, and timing are specified).
The primary estimator or model is clearly specified (e.g., OLS, logistic regression, ANCOVA).
Is a power analysis or sample size justification included?
- Yes, with calculations and inputs
- Yes, but minimal detail
- No
- Not applicable
Rank the following potential threats to interpretability for this study, from most to least concerning.
- Measurement error / instrument validity
- Confounding / selection bias
- Noncompliance / attrition
- Selective reporting / researcher degrees of freedom
- Model misspecification
- Multiplicity / p-hacking
Overall, how clear is the pre-analysis plan as currently written?
Approximately how long did you spend reviewing the materials today?
- Less than 15 minutes
- 15–30 minutes
- 31–60 minutes
- 1–2 hours
- More than 2 hours
What is your primary role?
- Academic researcher
- Graduate student
- Data scientist / analyst
- Policy researcher / evaluator
- Practitioner / NGO
- Other
Thank you for your thoughtful review. Your feedback will be used to improve the clarity and pre-specification of this plan before data collection begins.
What best describes the planned study design?
- Randomized controlled trial
- Quasi-experimental (e.g., DiD, IV, RD)
- Observational cross-sectional
- Longitudinal / panel study
- Lab / online experiment
- Qualitative or mixed methods
- Other
Each hypothesis specifies the expected direction of the effect.
Measurement instruments or scales are described in sufficient detail to be replicated.
Key assumptions of the chosen model are stated and justified.
Given the planned tests, how adequate is the statistical power justification?
Are there ethical considerations that may influence analysis choices? Select all that apply.
- None noted
- Privacy or data security risk
- Potential harm to participants
- Equity/fairness bias concerns
- Data governance/consent constraints
- Other
Based on your review, is this plan ready to proceed to data collection?
- Yes, proceed as planned
- Mostly ready; minor edits recommended
- Hold; needs substantive revisions
- Unsure
How many years of experience do you have with preregistrations or pre-analysis plans?
- Less than 1 year
- 1–3 years
- 4–6 years
- 7–10 years
- More than 10 years
In your own words, summarize the research question in one or two sentences.
Primary and secondary/exploratory hypotheses are clearly distinguished.
Secondary outcomes and any index/composite construction rules are clearly specified.
Robustness checks or sensitivity analyses are pre-specified.
If applicable, note the minimum detectable effect (MDE), key inputs, or any concerns about the power justification.
Which additions would most improve reproducibility before data collection? Select up to three.
- Mock registry entry (final wording)
- Code template or skeleton analysis script
- Data schema / variable naming plan
- Versioned package/dependency list
- Defined file/folder structure with README
- Plan for where materials will be shared
- Other
What are your most actionable suggestions to improve the clarity, pre-specification, or reproducibility of this plan?
What is your primary field or domain?
- Economics
- Political science
- Public health
- Education
- Psychology
- Sociology
- Computer science / data science
- Other
How well do the planned statistical tests align with the stated hypotheses?
Which types of outcomes are planned? Select all that apply.
- Behavioral / administrative
- Survey scale or index
- Physiological / biomarker
- Derived composite/index
- Binary event
- Time-to-event
- Other
Is the estimand (e.g., ATE, ITT, CACE) explicitly defined?
- Yes, clearly defined
- Partially defined
- Not defined
- Not applicable
Based on your responses, we'd like to explore your key recommendations in more depth. Please share your thoughts with our AI moderator.
Have you previously authored a preregistration or pre-analysis plan?
- Yes
- No
Please note any hypotheses that seem ambiguous, double-barreled, or underspecified, and briefly explain why.
How familiar are you with this study's topic area?
- Novice
- Intermediate
- Advanced
- Expert
What’s included
AI follow-ups
Adaptive probes on open-ended answers that pull out detail a static form would miss.
Attention checks
Built-in safeguards against rushed answers and low-quality respondents.
AI-drafted copy
Wording, ordering, and branching written by the AI — tuned to your research goal.
Auto report
Themes, quotes, and a plain-English summary write themselves once responses come in.
Why this template
What this template is built to do — we found no directly comparable template from other survey tools to review.
What sets it apart
- Includes structured opinion-scale ratings covering hypothesis clarity, outcome definitions, estimator specification, and power justification, so reviewers score each dimension of pre-specification quality separately
- Uses an AI follow-up interview to probe a reviewer's key recommendations in more depth after they submit initial ratings, capturing reasoning that a static form would miss
- Captures reviewer context (role, years of experience with preregistrations, field, familiarity with topic) via dropdowns so responses can be weighted or segmented by reviewer expertise
- Ends with an auto-generated report summarizing clarity, completeness, and readiness-to-proceed judgments across multiple expert reviewers
Ready to launch?
Open this template in the editor. Every part is yours to change before the first respondent sees it.
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