Along with examples involving vocational interests and mathematics achievement, the authors describe a multiple regression based, pattern recognition procedure that can be used to identify a pattern of predictor scores associated with high scores on a criterion variable. This pattern is called the criterion pattern. After the criterion pattern has been identified, a second regression procedure can be used to estimate the proportion of variation attributable to the criterion pattern. Cross-validation can then be used to estimate the variation attributable to a criterion pattern derived from regression weights estimated in another sample. Finally, issues of criterion pattern invariance and interpretation are discussed.

This article uses definitions provided by Cronbach in his seminal paper for coefficient α to show the concepts of reliability, dimensionality, and internal consistency are distinct but interrelated. The article begins with a critique of the definition of reliability and then explores mathematical properties of Cronbach's α. Internal consistency and dimensionality are then discussed as defined by Cronbach. Next, functional relationships are given that relate reliability, internal consistency, and dimensionality. The article ends with a demonstration of the utility of these concepts as defined. It is recommended that reliability, internal consistency, and dimensionality each be quantified with separate indices, but that their interrelatedness be recognized. High levels of unidimensionality and internal consistency are not necessary for reliability as measured by α nor, more importantly, for interpretability of test scores.

This paper explores the phimax adjustment to phi. It shows phi/phimax to be a measure of relationship apart from its affiliation with phi. The adjustment when the variables are inversely related, phimin, is also considered. Next is a discussion of the relation between phi/phimax and kappa. The article ends with an analytical look at phi/phimax. Some findings of this exploration are: phi/phimax is an asymmetrical, equal-interval step function with ties to probability. Finally, phi/phimax is shown to be nonrobust in situations where it should be most useful.

The generalized binomial test (GBT) and ω indices are the most recent methods suggested in the literature to detect answer copying behavior on multiple-choice tests. The ω index is one of the most studied indices, but there has not yet been a systematic simulation study for the GBT index. In addition, the effect of the ability levels of the examinees in answer copying pairs on the statistical properties of the GBT and ω indices have not been systematically addressed as yet. The current study simulated 500 answer copying pairs for each of 1,440 conditions (12 source ability level × 12 cheater ability level × 10 amount of copying) to study the empirical power and 10,000 pairs of independent response vectors for each of 144 conditions (12 source ability level × 12 cheater ability level) to study the empirical Type I error rates of the GBT and ω indices. Results indicate that neither GBT nor ω inflated the Type I error rates, and they are reliable to use in practice. The difference in statistical power of these two methods was very small, and GBT performs slightly better than does ω. The main effect for the amount of copying and the interaction effect between source ability level and the amount of copying are found to be very strong while all other main and interactions effects are negligible.