stats-test-pickerlisted

# Stats Test Picker Never name a test before answering these three questions: 1. What is the outcome type? (continuous / binary / count / ordinal / time-to-event) 2. How many groups or variables, and are they independent or paired? 3. What is the actual question: difference, association, equivalence, or non-inferiority? ## Decision path **Comparing means of 2 independent groups (continuous outcome):** - n < ~50 per group or visible skew: Mann-Whitney U - Else Welch's t-test (default over Student's; unequal variances are the norm) - Report: difference in means with CI, not just p **Paired/repeated measures:** Wilcoxon signed-rank if differences are skewed; paired t otherwise **3+ groups:** Kruskal-Wallis or one-way ANOVA; follow up with pairwise tests corrected via Holm, never raw **Binary outcome, 2 groups:** - Check expected cell counts; all >= 5: two-proportion z or chi-square without Yates - Small cells: Fisher exact - Large n and interested in direction with CI: report risk difference and ratio, not just chi-square **Count outcomes:** Poisson/negative binomial regression if covariates exist; else compare rates **Time-to-event:** log-rank test + hazard ratio with CI. Never compare mean survival times directly under censoring. ## Assumption checks that actually matter - Normality: do not Shapiro-test into paralysis. With n >= 50 per group prefer rank tests only for heavy skew (>1.5) or visible bimodality - Independence is NOT testable from the data: ask how it was