Presents a construction method for all factors that satisfy the assumptions of the model for factor analysis, including partially determined factors where certain error variances are zero. Illustrates that variable elimination can have a large effect on the seriousness of factor indeterminacy. (SLD)

This article provides a framework for reporting internal consistency reliability in counseling research and other related social science fields, including guidelines relative to score reliability coefficients and associated confidence intervals for both full sample and subgroups. Follow-up techniques for investigating low score reliability are…

Established a new criterion for the identification of recursive linear models in which some errors are correlated. Shows that identification is assured as long as error correlation does not exist between a cause and its direct effect; no restrictions are imposed on errors associated with indirect causes. (SLD)

Sees soft data, measures having substantial intrasubject variability due to errors of measurement or response inconsistency, as important measures of response in randomized clinical trials. Shows that using intensive design and slope of response on time as outcome measure maximizes sample retention and decreases within-group variability, thus…

Proposes true score models that can account for correlated errors and their effect on coefficient alpha. These models allow random measurement errors on earlier items to affect directly or indirectly the scores on later items. Conditions under which coefficient alpha may yield spuriously high estimates or reliability are discussed. (SLD)

Two tests for the jackknife autocorrelation estimator r(Q2) are evaluated. It is shown that a test based on the conventional approach for estimating the standard error of a jackknife estimator leads to unacceptable Type I error. An alternative approach is proposed that leads to a more satisfactory test when n>20. (Author/SLD)

Proposes a revised index of interrater agreement for multi-item ratings of a single target. This index is an inverse linear function of the ratio of the average obtained variance to the variance of the uniformly distributed random error. Discusses the importance of sample size for the index. (SLD)

Explains why, when one is using a bootstrapping approach for generating empirical standard errors for parameters of interest, the researchers must choose to fix an indicator path rather than the latent variable variance for the empirical standard errors to be generated properly. (SLD)

It is known that nonnormality, a heteroscedastic error term, or a nonlinear association can create serious practical problems when using the conventional analysis of covariance (ANCOVA) method. This article describes a simple ANCOVA method that allows heteroscedasticity, nonnormality, nonlinearity, and multiple covariates. When standard…

Measurement error is a common theme in classical measurement models used in testing and assessment. In classical measurement models, the definition of measurement error and the subsequent reliability coefficients differ on the basis of the test administration design. Internal consistency reliability specifies error due primarily to poor item…

Two unresolved implementation issues with logistic regression (LR) for differential item functioning (DIF) detection include ability purification and effect size use. Purification is suggested to control inaccuracies in DIF detection as a result of DIF items in the ability estimate. Additionally, effect size use may be beneficial in controlling…

We designed a series of analyses to develop a measurement system capable of simultaneously recording the free-play patterns of 20 children in a preschool classroom. Study 1 determined the intermittency with which the location and engagement of each child could be momentarily observed before the accuracy of the measurement was compromised. Results…

In this study, the authors develop a generalized multilevel facets model, which is not only a multilevel and two-parameter generalization of the facets model, but also a multilevel and facet generalization of the generalized partial credit model. Because the new model is formulated within a framework of nonlinear mixed models, no efforts are…

This paper presents a new polychoric instrumental variable (PIV) estimator to use in structural equation models (SEMs) with categorical observed variables. The PIV estimator is a generalization of Bollen's (Psychometrika 61:109-121, 1996) 2SLS/IV estimator for continuous variables to categorical endogenous variables. We derive the PIV estimator…

The use of value-added models in education research has expanded rapidly. These models allow researchers to explore how a wide variety of policies and measured school inputs affect the academic performance of students. An important question is whether such effects are sufficiently large to achieve various policy goals. Judging whether a change in…