In multiple regression analysis, where resulting predictive equation effectiveness is subject to shrinkage, it is especially important to evaluate result replicability. Double cross-validation is an empirical method by which an estimate of invariance or stability can be obtained from research data. A procedure for double cross-validation is…

An investigation of the effects of randomly missing data in two-predictor regression analyses is described. The differences in the effectiveness of five common treatments of missing data on estimates of R-squared values and each of the two standardized regression weights is also investigated. Bootstrap sample sizes of 50, 100, and 200 were drawn…

Quantitative methods for research synthesis usually involve calculation of an estimate of effect size for each of a series of studies. Some problems associated with ad hoc methods of analysis, such as ordinary least squares regression analysis using estimates of effect size, are described. (Author/JKS)

Eight formula-based estimates of population squared cross-validity and nine estimates of factor scores were compared with estimates from the conventional cross-validation procedure. Burket's and Rozeboom's formula-based estimates of population squared cross-validity in combination with a factor score method offer the most for practitioners…

A review of cross-validation shrinkage formulas is presented which focuses on the theoretical and practical problems in the use of various formulas. Practical guidelines for use of both formulas and empirical cross-validation are provided. A comparison of results using these formulas in a range of situations is then presented. The result of these…

A method for the estimation of covariance structure models under polynomial constraints (such as quadratic constraints) is presented. Estimation is on maximum likelihood principles, and the test statistics, parameter estimates, and standard errors are based on a statistical theory which takes the constraints into account. (Author/JKS)

Aside from the theoretical issues involving the validity of inferences from surveys, the basic problem of producinq unbiased estimates of regression parameters and estimates of the associated standard errors has been a particularly difficult issue in dealing with results from stratified multistage sample designs such as the one used in the…

Two approaches for conceptualizing and estimating a contextual model for analyzing student achievement are the separate equation approach and the single equation approach. The separate equation method determines the relationship between the individual-level independent variable and the individual-level dependent variable within each group. It then…

This paper explores various procedures of panel data in the estimation of causal models. The reported analyses are from the Monitoring the Future study, a nationwide questionnaire survey of 16,000 to 17,000 high school seniors conducted annually since 1975. First, the parameters of causal models are estimated in which the dependent variables are…