R Biostatistics Cheat Sheets
Twelve concise, code-first references for clinical research and reproducible biostatistics. Every PDF is free to download and includes review checks, reporting guidance and runnable R patterns.
12 references
Clinical regression
Choose an outcome model, encode predictors, diagnose fit and report effects.
Survival analysis
Kaplan-Meier, log-rank, Cox models, proportional hazards and censoring.
Diagnostic accuracy
2 × 2 metrics, predictive values, likelihood ratios, ROC curves and bias.
Effect sizes & reporting
Match effects to designs and pair estimates with confidence intervals.
Missing data
Audit missingness, configure MICE, pool models and run MNAR sensitivity checks.
Mixed models
Random effects, marginal means, clustered outcomes and model diagnostics.
Power & sample size
Design inputs, attrition, cluster inflation, sensitivity grids and simulation.
Repeated measures
Paired tests, baseline-adjusted ANCOVA, longitudinal models and missing visits.
Clinical trial analysis
Estimands, analysis sets, adjusted effects, subgroups and sensitivity analyses.
Scale development & validation
Item audits, polychoric correlations, EFA, ordinal CFA, reliability and scoring.
Causal inference
Target trials, DAG logic, positivity, IPTW, balance and standardization.
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