Parallel analysis has been considered one of the most accurate methods for determining the number of factors in factor analysis. One major advantage of parallel analysis over traditional factor retention methods (e.g., Kaiser's rule) is that it addresses the sampling variability of eigenvalues obtained from the identity matrix, representing the…

The gold standard for identifying more effective pedagogical approaches is to perform an experiment. Unfortunately, frequently a hypothesized alternate way of teaching does not yield an improved effect. Given the expense and logistics of each experiment, and the enormous space of potential ways to improve teaching, it would be highly preferable if…

Exploratory factor analysis involves five key decisions. The second decision, how many factors to retain, is the focus of the current paper. Extracting too many or too few factors often leads to devastating effects on study results. The advantages and disadvantages of the most effective and/or most utilized strategies to determine the number of…

Distributional characteristics of the measure of sampling adequacy (MSA) were investigated in sample correlation matrices generated from multivariate normal populations with covariance matrix equal to the identity. Systematic variation of sample size and number of variables resulted in minimal fluctuation of the overall MSA from .50. (Author/RC)

Problems of sampling error and accumulated rounding error in canonical variate analysis are discussed. A new technique is presented which appears to be superior to canonical variate analysis when the ratio of variables to sampling units is greater than one to ten. Examples are presented. (Author/JKS)

An alternative derivation of Tryon's basic formula for the coefficient of domain validity or the coefficient of generalizability developed by Cronbach, Rajaratnam, and Glaser is provided. This derivation, which is also the generalized Kuder-Richardson coefficient, requires a relatively minimal number of assumptions compared with that in previously…

This paper presents the generalized symmetric means approach to the estimation of population covariances, complete with derivations and examples. Particular attention is paid to the problem of missing data, which is handled very naturally in the incidence sampling framework. (CTM)

Investigated empirically through post mortem item-examinee sampling were the relative merits of two alternative procedures for allocating items to subtests in multiple matrix sampling and the feasibility of using the jackknife in approximating standard errors of estimate. The results indicate clearly that a partially balanced incomplete block…

Considers a class of estimation procedures for the factor model. The procedures are shown to yield estimates possessing the same asymptotic sampling properties as those from estimation by maximum likelihood or generalized last squares, both special members of the class. General expressions for the derivatives needed for Newton-Raphson…

The effect of stratified sampling of items on the estimation of test score distribution parameters by multiple matrix sampling was studied. Item difficulty and/or interitem correlations were the bases of stratification. Various item iniverses were created by computer simulation and sampled according to several plans. The results indicate that…

In some correlational studies it is not reasonable to assume that bivariate observations are uncorrelated. An example would be a configural analysis in which two individuals are correlated across several variables (e.g., Q-technique). The present study was a Monte Carlo investigation of the robustness of techniques used in judging the magnitude of…

Multiple matrix sampling (MMS) procedures were utilized to determine the necessary parameters of a Pearson Type I curve. Empirical norms distributions were approximated by both the Type I model and the negative hypergeometric model. Four existing ITED norms distributions, two subtests and two grades, were approximated by the MMS procedures. Two…