Point‐biserial correlation: Interval estimation, hypothesis testing, meta‐analysis, and sample size determination

Hypothesis Testing and Interval Estimation

1 Topics for this Module 1. An Idealistic Special Case — When is Known. 2. Con…dence Interval Estimation (a) Taking a Stroll with Mr. Mu 3. Hypothesis Testing (a) Parameter Spaces and Sample Spaces (b) Partitioning the Parameter Space (c) Partitioning the sample space (d) Raw Score Rejection Rules (e) Error Rates i. Type I Error ii. Type II Error (f) Statistical Power i. Power vs. Precision 4. ...

Large Sample Estimation and Hypothesis Testing*

Bayesian sample size determination under hypothesis tests.

We develop a Bayesian approach for calculating sample sizes for clinical trials under the framework of hypothesis tests. We extend the work of Weiss (The Statistician 1997; 46: 185-191) to include composite distributions for the treatment effect and the variance of the data within the null and alternative hypotheses. We select sample sizes using the Bayes factor and the averaged type I error an...

Sample Size Reassessment and Hypothesis Testing in Adaptive Survival Trials

Mid-study design modifications are becoming increasingly accepted in confirmatory clinical trials, so long as appropriate methods are applied such that error rates are controlled. It is therefore unfortunate that the important case of time-to-event endpoints is not easily handled by the standard theory. We analyze current methods that allow design modifications to be based on the full interim d...

Sample size estimation in epidemiologic studies

This review basically provided a conceptual framework for sample size calculation in epidemiologic studies with various designs and outcomes. The formula requirement of sample size was drawn based on statistical principles for both descriptive and comparative studies. The required sample size was estimated and presented graphically with different effect sizes and power of statistical test at 95...