statistical-power

Adaptive Bayesian Clinical Trial

PRISME Power Calculator

Statistical power analyses in the browser

Power and Sample Size Calculation for the Cochran-Mantel-Haenszel Chi-Squared Test

Code for "Adaptive Selection of the Optimal Strategy to Improve Precision and Power in Randomized Trials"

Find out which qualities of your writing actually predict engagement. Rates every post you have published against a pre-registered rubric using Jev's calibrated judgments, then tests those ratings against your real engagement numbers. Refuses to report findings your sample cannot support.

This incomplete repository is used to facilitate the consultation of individual files in this project. Only files smaller than 100 MB are available here. The complete project is available at https://doi.org/10.17605/OSF.IO/GT5UF.

How many runs before your eval means anything? Reliability statistics for stochastic evals: audit miss rates, exact intervals, runs-needed.

Assay-aware observability, donor-level power and design adequacy for single-cell alternative splicing

A probe suite that measures which conversation states an LLM cannot leave. Three arms, because two cannot tell obedience from token statistics; a null only counts when the design had the power to see the effect.

A/B test analyzer that returns ship/hold/iterate/kill, not a p-value. Power vs a pre-specified MDE, CIs, effect size, and SRM checks on every result. 37 tests.

Identifying and avoiding common misinterpretations in using statistics

Applied statistics casebook: A/B-testing business cases (ROI, MDE, Bonferroni, selection bias) with decks, plus a 12-part statistical inference workbook

Eval suites that tell you when they've gone blind: coverage, detection power and judge depth for LLM agent evaluation.

Simulation studies of power and Type I error of mass univariate statistics for ERP data

What a 1,450-test tail-predictor search could have detected: a power accounting, and a tail-IC/mean-IC pre-registration gate. Companion to Yan (2026).

Your prompt eval cannot detect what you think it can. Ship-the-higher-number declares a winner 46.6% of the time on identical variants; detecting +5pp at 80% power needs ~859 items. Measured by simulation, re-measured in CI.

This module allows running Power Analyses in JASP

Size your early-stopping window by statistical power instead of by habit

Reproducible statistical-power simulation suite for adaptive studies with an embedded active-inference agent: multiple-testing corrections, sequential e-processes, and action-loop operating characteristics, using real pymdp inference.