- 期刊
Extending the A Priori Procedure to Normal Bayes Models
摘要
The a priori procedure (APP) was designed as a pre-data procedure whereby researchers could find the sample sizes necessary to ensure that sample statistics to be obtained are within particular ranges of corresponding population parameters with known probabilities. Although the APP has been devised for a variety of experimental paradigms, these have all concerned parameters in classical statistics. The present work extends a priori thinking to an important case not addressed previously, where the researcher is interested in estimation in normal Bayes models. Computer simulations support the equations presented, along with a real data example for illustration of our main results.
延伸閱讀
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