Educational articles about Simon's two-stage design, power functions, phase II trial design selection, sample size, early stopping, and BioStatHub workflows.
12 min read | Beginner
A practical introduction to Simon's two-stage design for single-arm phase II trials, including early stopping, minimax and optimal designs, and practical tradeoffs.
10 min read | Beginner
A practical guide to selecting p₀ and p₁ for Simon two-stage designs, including the effect size concept, the four-way trade-off with α and β, and an iterative workflow for finding a feasible design.
10 min read | Beginner
A practical guide to choosing α and β in a Simon two-stage design, including their clinical interpretation, effect on sample size, common choices, and how to justify them in a Phase II protocol.
10 min read | Beginner
Explains why Phase II trials use prospective futility rules, how Simon’s two-stage design balances patient protection with statistical power, and how PET and ESS make the benefit visible.
14 min read | Beginner
Explains how single-arm Phase II trials evaluate activity against a predefined benchmark, why historical comparability matters, and how two-stage designs support efficient development decisions.
10 min read | Intermediate
A practical guide to choosing between Simon's Optimal and Minimax two-stage designs by comparing expected sample size under p₀, early stopping, maximum enrollment, and the rationale behind each optimization objective.
10 min read | Intermediate
Explains how admissible designs form the Pareto frontier between Simon's optimal and minimax designs, and when a compromise design may be preferable.
12 min read | Intermediate
Learn how to choose among Optimal, Minimax, and admissible Simon two-stage designs by comparing expected sample size, maximum sample size, early stopping, and operational priorities.
9 min read | Intermediate
Explains probability of early termination (PET), how it is calculated, why it depends on the true response rate, and how it balances with expected sample size, power, and type I error in Simon's two-stage designs.
8 min read | Intermediate
Explains how expected sample size depends on the response probability, how it relates to probability of early termination, and how it can help compare Simon's two-stage designs.
7 min read | Beginner
A workflow tutorial that connects the educational concepts to the BioStatHub calculator, final design review, and report export.
10 min read | Intermediate
Explains how the power function incorporates Stage 1 futility stopping and the final response rule, and how power curves help investigators compare and select Simon two-stage designs.