Scenario Guide

Use this guide to pick a module and test for your study design.

Implemented scenarios (48 tests)

Module Tests
biomarker 7
clinical 11
workspace 30

Power Workspace (30 tests)

Classical families: t, F, chi-square, exact proportions, z correlations/GLM, Wilcoxon rank tests.

Biomarker Discovery (7 tests)

ROC/AUC, diagnostic accuracy, log-rank, Cox, FDR screening, differential expression.

Clinical Trials (11 tests)

Superiority, NI, equivalence (TOST), Simon two-stage, cluster RCT, multi-arm ANOVA, Poisson counts, survival.

Decision table

Study question Module Example test
Two-group mean difference Power Workspace or Clinical t_two_sample, rct_superiority_continuous
Paired / pre-post Power Workspace t_paired
One-way ANOVA Power Workspace or Clinical f_anova_one_way, multi_arm_superiority
Multiple regression \(R^2\) Power Workspace f_mreg_omnibus
Two proportions (Fisher) Power Workspace or Clinical exact_fisher, rct_superiority_binary
McNemar paired proportions Power Workspace exact_mcnemar
Correlation difference Power Workspace z_corr_independent
Logistic / Poisson GLM Power Workspace or Clinical z_logistic, count_endpoint_poisson
Biomarker AUC Biomarker roc_auc_one
Diagnostic sens/spec Biomarker diagnostic_acc
Survival / HR Biomarker or Clinical cox_regression, survival_pmu
Non-inferiority trial Clinical rct_noninferiority_continuous
Bioequivalence (TOST) Clinical rct_equivalence_continuous
Oncology Phase II Simon Clinical simon_two_stage
Cluster RCT Clinical cluster_rct
Omics screening + FDR Biomarker discovery_fdr

Not yet implemented

Document for planning only — use external tools or custom simulation:

  • Group sequential / interim analyses
  • Crossover or repeated-measures RCT
  • Dunnett pairwise multi-arm comparisons
  • Paired / correlated ROC comparison
  • Partial AUC, NPV/PPV as primary endpoints
  • Time-varying accrual and dropout in survival
  • Bayesian assurance
  • Simon optimal design search (minimax / optimal)