The effect of large, within-examinee item difficulty variability on estimates of the proportion of consistent classification of examinees into mastery categories was studied over 2 test administrations for 100 simulated examinees. The proportion of consistent classifications was adequately estimated using the technique proposed by M. Subkoviak…

The utility of the fail-safe "N" statistic was evaluated by computing it for studies in three organizational research domains in which discrepant conclusions were reached by initial and subsequent meta-analyses. Calculation of the fail-safe "N" may have led to more cautious interpretations. Implications for meta-analyses are…

A model is proposed for investigating test validity as a predictor of a criterion variable when there are both missing and censored scores in the data set. Implications for maximum likelihood estimation are discussed, and the method is illustrated with hypothetical data sets. (SLD)

A model for student retention and attrition is presented. Focus is on alternative models for the "dampening" in attrition rates as educational programs progress. Maximum likelihood estimates for the underlying parameters in each model and a Bayesian analysis are provided. (TJH)

An empirical sampling approach was used to assess the accuracy of a Taylor approximation for the estimation of sampling errors. The sampling errors were in the statistics involved in estimating a path model based on medium-sized samples gathered using five sample designs commonly used in educational research. (TJH)

Path Analysis of Covariance Matrix (PACM) is described as a way to separately estimate measurement and structural models using standard least squares procedures. PACM was empirically compared to simultaneous maximum likelihood estimation and use of the LISREL computer program, and its advantages are identified. (SLD)

Establishes a theoretical basis for both understanding and testing the molecular level assumptions in mixtures. Considers activity coefficient models and equation of state mixing rules. (YP)

Situations for which the researcher should use component analysis versus common factor analysis are discussed. Topics addressed include key algebraic similarities and differences, theoretical and practical issues, the factor indeterminacy issue, latent versus manifest variables, and differences between exploratory and confirmatory analysis…

The empirical performance under null/alternative hypotheses of the likelihood ratio difference test (LRDT); Lagrange Multiplier test (evaluating the impact of model modification with a specific model); and Wald test (using a general model) were compared. The new tests for covariance structure analysis performed as well as did the LRDT. (RLC)

The equating methods and sampling designs used in the empirical studies in this special issue on the use of matched samples for test equating are described. Four requisites for equating are listed, and the invariance of equating functions requisite is identified as the focus of this issue. (SLD)

Illustrates how heuristics can provide a psychological narrative of Hippocrates' and Archytas' thinking on the duplication of the cube. Four general heuristic techniques were used. (YP)

The neuronal model shown to code sound-source azimuth in the barn owl by H. Wagner et al. in 1987 is used as the basis for a speculative brain-based human model, which can establish contrastive phonetic categories to solve the problem of perception "non-invariance." (SLD)

A method is proposed for equating different sets of items administered to different groups using the Rasch model. The Rasch equating model formulated describes one common Rasch scale in different groups with different but overlapping item sets. The model, based on the quasi-loglinear Rasch model, can be tested globally. (SLD)

Explores the use of computers for teaching mathematical models of transposition ciphers. Illustrates the ideas, includes activities and extensions, provides a mathematical model and includes computer programs to implement these topics. (MVL)

A stochastic version of a knowledge space is developed in which knowledge states are considered as possible epochs in a subject's learning history. It specifies how a subject is channeled through and progresses along a "gradation." The model's application to artificial data is described, based on maximum likelihood methods. (TJH)