A Bayesian One-Sample Test for Proportion

Jeffreys Interval for One-Sample Proportion with SAS/STAT Software

This paper introduces Jeffreys interval for one-sample proportion using SAS® software. It compares the credible interval from a Bayesian approach with the confidence interval from a frequentist approach. Different ways to calculate the Jeffreys interval are presented using PROC FREQ, the QUANTILE function, a SAS program of random walk Metropolis sampler, and PROC MCMC.

One-Sample Hypothesis Test Examples

Tests for One Proportion

Introduction The One-Sample Proportion Test is used to assess whether a population proportion (P1) is significantly different from a hypothesized value (P0). This is called the hypothesis of inequality. The hypotheses may be stated in terms of the proportions, their difference, their ratio, or their odds ratio, but all four hypotheses result in the same test statistics. For example, suppose tha...

A mixed Bayesian/Frequentist approach in sample size determination problem for clinical trials

In this paper we introduce a stochastic optimization method based ona mixed Bayesian/frequentist approach to a sample size determinationproblem in a clinical trial. The data are assumed to come from a nor-mal distribution for which both the mean and the variance are unknown.In contrast to the usual Bayesian decision theoretic methodology, whichassumes a single decision maker, our method recogni...

Test for Exponentiality Based on the Sample Covariance

This paper proposes a simple goodness-of-fit test based on the sample covariance. It is shown that this test is preferable for alternatives of increasing and unimodal failure rate. Critical values for various sample sizes are determined by means of Monte Carlo simulations. We compare the test based on the sample covariance with tests based on Hoeffding's maximum correlation. The usefulness o...