Transformations or equating of raw test scores on two or more forms of the same test are made interchangeable by empirical procedures deriving the standard error of an equipercentile equating for four different situations. Some numerical results are checked by Monte Carlo methods. Numerical standard errors are computed for two sets of real data.…

Classification studies are important for practitioners who need to identify individuals for specialized treatment or intervention. When interventions are irreversible or misclassifications are costly, information about the proficiency of different classification procedures becomes invaluable. This study furnishes information about the relative…

A Monte Carlo study was conducted to compare the statistical bias and standard errors of non-equivalent-groups linear test equating in small samples of examinees. One thousand samples of each size (15, 25, 50, and 100) were drawn with replacement from each of five archival data files from elementary school and secondary school teacher subject area…