When norming tests, it may be preferable to use the matrix sampling technique. The results from the samples may be used to estimate what the distribution of scores would have been if each subject had taken all the items. This paper compares four methods for making these estimates. The sample size made it possible to compare the techniques in a…

Two psychometric models are presented for evaluating the difficulty of the distractors in multiple-choice items. They are based on the criterion of rising distractor selection ratios, which facilitates interpretation of the subject and item parameters. Statistical inferential tools are developed in a Bayesian framework: modal a posteriori…

In a situation where the population distribution of latent trait scores can be estimated, the ordinary maximum likelihood estimator of latent trait scores may be improved upon by taking the estimated population distribution into account. In this paper empirical Bayes estimators are compared with the liklihood estimator for three samples of 300…

This report describes new statistical procedures for item response analysis using estimation of item response curves used in mental testing with ability parameters treated as a random sample. Modern computer technology and the EM algorithm make this solution possible. The research focused on the theoretical formulation and solution of maximum…

Formulas are presented for decision reliability and for classification validity for mastery/nonmastery decisions based on criterion referenced tests. Two item parameters are used: the probability of a master answering an item correctly, and the probability of a nonmaster answering an item incorrectly. The theory explores the relationships of…

Thirty-four papers on educational statistics which were presented at the 1971 AERA Conference are summarized. Six major interest areas are covered: (a) general information; (b) non-parametric methods; (c) errors of measurement and correlation techniques; (d) regression theory; (e) univariate and multivariate analysis; (f) factor analysis. (MS)