An exploratory method for determining measurement design based on the posterior predictive distribution

Abstract

In this article, an exploratory method for determining repeated measurement design based on the posterior predictive distribution is proposed. By sampling the future observations repeatedly via the posterior predictive distribution, we can determine the measurement design necessary for the mean range of confidence interval of true scores falls within a prespecified value with a certain probability. This method takes into account uncertainty about the true parameter values, and can be carried out with introductory programming skills. This method is applicable to various situations in psychological research although it may take a long time for computation in certain conditions.