We review common situations in Bayesian latent variable models where the prior distribution that a researcher specifies differs from the prior distribution used during estimation. These situations can arise from the positive definite requirement on correlation matrices, from sign indeterminacy of factor loadings, and from order constraints on…

Experiments allow researchers to randomly vary the key manipulation, the instruments of measurement, and the sequences of the measurements and manipulations across participants. To date, however, the advantages of randomized experiments to manipulate both the aspects of interest and the aspects that threaten internal validity have been primarily…

This article is concerned with the question of whether the missing data mechanism routinely referred to as missing completely at random (MCAR) is statistically examinable via a test for lack of distributional differences between groups with observed and missing data, and related consequences. A discussion is initially provided, from a formal logic…

This report summarizes the complex research literature on quantitative methods for assessing how impacts of educational interventions on instructional practices and student learning differ across students, educators, and schools. It also provides technical guidance about the use and interpretation of these methods. The research topics addressed…

Assessing the correctness of a structural equation model is essential to avoid drawing incorrect conclusions from empirical research. In the past, the chi-square test was recommended for assessing the correctness of the model but this test has been criticized because of its sensitivity to sample size. As a reaction, an abundance of fit indexes…

This paper presents a research agenda for a funded research project on knowledge sharing among academics in Malaysia. One of the main objectives is to develop validate and measure of knowledge sharing which is suitable for academicians. Previous studies on knowledge sharing have used standard measurement items which do not cater for the multiple…

Researchers using structural equation modeling (SEM) aspire to learn about the world by seeking models with causal specifications that match the causal forces extant in the world. This quest for a model matching existing worldly causal forces constitutes an ontology that orients, or perhaps reorients, thinking about measurement validity. This…

A structural equation modeling based method is outlined that accomplishes interval estimation of individual optimal scores resulting from multiple-component measuring instruments evaluating single underlying latent dimensions. The procedure capitalizes on the linear combination of a prespecified set of measures that is associated with maximal…

Amos 5.0 (Arbuckle, 2003) permits exploratory specification searches for the best theoretical model given an initial model using the following fit function criteria: chi-square (C), chi-square--df (C--df), Akaike Information Criteria (AIC), Browne-Cudeck criterion (BCC), Bayes Information Criterion (BIC) , chi-square divided by the degrees of…

Presents a validation procedure for cognitive structures that is based on structural equation modeling of cognitive subordination relationships among test items. Illustrates the method using scores of 278 ninth graders on an algebra test and shows results for the same test when the linear logistic test model is used. (SLD)

Demonstrates empirically a structural equation modeling technique for group comparison of reliability and validity. Data, which are from a study of 495 mothers' attitudes toward pregnancy, have a one-factor measurement model and three sets of subpopulation comparisons. (SLD)