Using a computer-based Monte Carlo approach to generate item responses, the results of this study indicate that, when item discrimination indices are considered, item-examinee sampling procedures having the same number of observations have different standard errors in estimating both test mean and test variance. With certain types of tests, a…

The meaningful investigation of many problems in statistics can be solved through Monte Carlo methods. Monte Carlo studies can help solve problems that are mathematically intractable through the analysis of random samples from populations whose characteristics are known to the researcher. Using Monte Carlo simulation, the values of a statistic are…

It is the purpose of this paper to provide social scientists with some insight in dealing with Type 11 error, that is, the probability of failing to reject a false null hypothesis, and therefore, optimum sample size and number of levels, in the random-effects analysis of variance. (Author/RK)

Copies of a source listing of this program can be obtained by writing to author at Ohio University, Athens, Ohio. (MB)

In most behavioral science research very little attention is ever given to the probability of committing a Type II error, i.e., the probability of failing to reject a false null hypothesis. Recent publications by Cohen have led to insight on this topic for the fixed-effects analysis of variance and covariance. This paper provides social scientists…