Composite scores are an exceptionally important psychometric tool for behavioral science research applications. A prototypical example occurs with self-report data, where researchers routinely use questionnaires with multiple items that tap into different features of a target construct. Item-level missing data are endemic to composite score…

The UCLA National Center for Research on Evaluation, Standards, and Student Testing (CRESST) is under contract from the Naval Postgraduate School (NPS) to conduct research on assessment models and tools designed to support Marine Corps rifle marksmanship. In this deliverable, we first review the literature on known-distance rifle marksmanship…

Evaluated the use of Mallow's C(p) and Wherry's adjusted R squared (R. Wherry, 1931) statistics to select a final model from a pool of model solutions using computer generated data. Neither statistic identified the underlying regression model any better than, and usually less well than, the stepwise selection method, which itself was poor for…

Regression analysis is one of the more common analytic tools used by researchers. However, multicollinearity between the predictor variables can cause problems in using the results of regression analyses. Problems associated with multicollinearity include entanglement of relative influences of variables due to reduced precision of estimation,…

A method for estimating the first eigenvalue of random data correlation matrices is reported, and its precision is demonstrated via comparison to the method of S. J. Allen and R. Hubbard (1986). Data generated in Monte Carlo simulations with 10 sample sizes reaching up to 1,000 were used. (SLD)

A strategy is proposed for conceptualizing moderating relationships based on their type (strictly correlational and classically correlational) and form, whether continuous, noncontinuous, logistic, or quantum. Results of computer simulations comparing three statistical approaches for assessing moderator variables are presented, and advantages of…

Performance of the logistic regression (LR) procedure was compared to that of the Mantel Haenszel (MH) procedure in the detection of uniform and nonuniform differential item functioning on a simulation examining distributional properties of the LR and MH test statistics and the relative power of the two procedures. (SLD)

This study investigates parameter estimation under the simple linear regression model for situations in which the underlying assumptions of ordinary least squares estimation are untenable. Classical nonparametric estimation methods are directly compared against some robust estimation methods for conditions in which varying degrees of outliers are…

A method is presented for estimating the item characteristic curve (ICC) using polynomial regression splines. Estimation of spline ICCs is described by maximizing the marginal likelihood formed by integrating ability over a beta prior distribution. Simulation results compare this approach with the joint estimation of ability and item parameters.…

P. O. Johnson and J. Neyman (1936) proposed a general linear hypothesis testing procedure for testing the null hypothesis of no treatment difference in the presence of some covariates. This is generally known as the Johnson-Neyman (JN) technique. The need for the hypothesis testing step (often omitted) as originally presented and the…

Ridge estimates (REs) of population beta weights were compared to ordinary least squares (OLS) estimates through computer simulation to evaluate the use of REs in explanatory research. With fixed predictors, there was some question of the consistency of ridge regression, but with random predictors, REs were superior to OLS. (SLD)

A logistic regression model for characterizing differential item functioning (DIF) between two groups is presented. A distinction is drawn between uniform and nonuniform DIF in terms of model parameters. A statistic for testing the hypotheses of no DIF is developed, and simulation studies compare it with the Mantel-Haenszel procedure. (Author/TJH)

A method is suggested to estimate the relationship between a latent trait and one or more manifest predictors without estimating subject parameters. The method, developed for the Rasch model, can be generalized to two-parameter and three-parameter logistic latent trait models. The model is illustrated with simulated and empirical data. (SLD)

A reduction in agricultural activity in a rural farming community will result in reduced activity in almost every sector of the local economy. The result may be measured in loss of employment and income. This report provides a method to estimate such economic impacts with a minimum of data collection and manipulation. Most of the input data…

The use of stepwise regression has been criticized for both interpretive misunderstandings and statistical aberrations. A major statistical problem with stepwise regression and other procedures that involve multiple significance tests is the inflation of the Type I error rate. General approaches to control the family-wise error rate such as the…