About EarlyReview

Why EarlyReview?

Pre-analysis plans are essential for credible research — but writing a good one is hard. Small omissions can create ambiguity later, and major gaps often only become obvious after you've already collected data, shared drafts, or submitted to a registry or journal.

EarlyReview provides structured feedback on your pre-analysis plan or registered report before you submit it. It identifies missing commitments, unclear specifications, and internal inconsistencies that increase researcher degrees of freedom and reviewer risk.

EarlyReview also gives you the option to share that your plan cleared external completeness and consistency checks — for example with funders, advisors, or collaborators.

What EarlyReview checks

EarlyReview focuses on the core elements that make a pre-analysis plan or registered report auditable:

• Research question and target population
• Treatment arms and assignment procedure (including unit of randomization)
• Primary outcomes and outcome timing
• Primary estimand and preferred specification
• Covariate adjustment plan
• Multiple hypothesis testing plan
• Heterogeneity analyses (or an explicit statement that none are planned)
• Attrition / missing-data handling
• Power or minimum detectable effect (MDE) statement
• Internal consistency across sections
• ...and more

Statistical power assessment

Beyond checking what's in your plan, EarlyReview assesses whether your study is likely to be well-powered. It forecasts plausible effect sizes for each outcome based on the intervention type, target population, and existing literature, then evaluates whether your stated sample size is sufficient to detect effects of that magnitude. This helps identify studies that may be underpowered before data collection begins.

Structured output

EarlyReview produces a structured representation of your commitments that you can verify — making your plan easier to reuse in downstream tools.

Contact

Questions or feedback? Reach out at contact@earlyreview.ai.