Four structured questions — outcome type, comparison structure, pairing, adjustment — mapped through a deterministic decision table to the recommended primary analysis. The answer leads with the estimand (what you will actually estimate and report), then the test, the assumptions to check, and the fallback if they fail.
What kind of study is this? (optional)
This is not a neutral lookup table — it encodes methodological positions that reviewers and statisticians hold, so the recommendation is defensible, not just common:
This is one of the same deterministic engines that power RigorMD’s paid reviews — exposed free here, the identical rule table, not a simplified preview of it.
Some designs need more than a table: cluster-randomized trials, non-inferiority and equivalence designs, Bayesian and adaptive designs, and any analysis where confounding strategy is the real question. If you tick “clustered,” the tool tells you a naïve test is wrong and a mixed-effects model or GEE is needed — it does not pretend the simple answer still holds. Where a question is beyond the table, the honest output is “this needs a biostatistician,” not a guess.
If you want that check done by a person, tell us below →.
The test is one line of an analysis plan. If you want a statistician to check the rest — hypotheses, the variables and confounders to collect, the sample-size arithmetic for your effect size, a draft IRB statistical-methods page — tell us, and we will let you know if we build it. For what reviewers check beyond test choice, see what a pre-submission statistical review covers →.