Two indices for assessing the efficiency of decisions in mastery testing are proposed. The indices are generalizations of the raw agreement index and the kappa index. Empirical examples of these indices are given. (Author/JKS)

Simulated data based on five test score distributions indicate that a slight modification of the asymptotic normal theory for the estimation of the p and kappa indices in mastery testing will provide results which are in close agreement with those based on small samples from the beta-binomial distribution. (Author/BW)

Techniques for classifying individuals into mastery or non-mastery status based on criterion-referenced test performance are investigated. Extensions of mastery classification techniques developed by Macready and Dayton are presented. The techniques are based on latent class and quasi-independence models. (Author/JKS)

A procedure is described for determining the minimal length of a mastery test given certain constraints. The procedure assumes that the testor is indifferent to misclassifying some testees who score within a specified range about the passing score. An example and table are provided. (JKS)

In the case of dichotomous decisions, the total set of all assumptions/specifications for which the decision would have been the same is the robustness region. Inspection of this (data-dependent) region is a form of sensitivity analysis which may lead to improved decision making. (Author/BW)

Descriptions are presented of two related probabilistic models that can be used for making classification decisions with respect to mastery of specific concepts or skills. Determination of cutoff scores, minimal number of items necessary, and the assessment of the quality of tests provided by the model are discussed. (Author/JKS)

In mastery testing, the raw agreement index and the kappa index may be estimated via one test administration when the test scores follow beta-binomial distributions. This paper reports formulae, tables, and a computer program which facilitate the computation of the standard errors of the estimates. (Author/CTM)

Taylor and Russell produced a set of tables which gives the proportion of successful cases when a given cutoff score or a predictor variable and the correlation between the predictor variable and the criterion are known. This paper extends this procedure to the case where parameters are not known. (Author/JKS)

False-positive and false-negative decisions are the two possible errors committed with a mastery test; yet the estimation of the likelihood of committing these errors has not been investigated. Two methods of this type of estimation are presented and discussed. (Author/JKS)

The Libby-Novick class of three-parameter generalized beta distributions is shown to provide a rich class of prior distributions for the binomial model that removes some restrictions of the standard beta class. A numerical example indicates the desirability of using these wider classes of densities for binomial models. (Author/BW)

Methods are described for obtaining upper and lower bounds to both false-positive and false-negative decisions with a mastery test. These methods make no assumptions about the form of the true score distribution. (CTM)

Two approaches, the minimax approach and the Rasch procedure, are described for the simultaneous determination of passing scores for subtests when the passing score for the total test is known. (Author/LMO)

Macready and Dayton introduced two probabilistic models for mastery assessment based on an idealistic all-or-none conception of mastery. Alternatively, an application of latent trait theory to mastery testing is proposed (a three parameter logistic model) as a more plausible model for test theory. (Author/CTM)

Procedures based on latent trait models and the Rasch model are described for computation and asymptotic statistical inference for two decision consistency indexes often used in mastery or competence testing. Simulations were conducted for typical mastery testing situations to illustrate the procedures. (SLD)