Nearly all quantitative analyses in higher education draw from incomplete datasets-a common problem with no universal solution. In the first part of this paper, we explain why missing data matter and outline the advantages and disadvantages of six common methods for handling missing data. Next, we analyze real-world data from 5,905 students across…

In educational research, a randomized controlled trial is the best design to eliminate potential selection bias in a sample to support valid causal inferences, but it is not always possible in educational research because of financial, ethical, and logistical constrains. One alternative solution is use of the propensity score (PS) methods.…

Researchers in career and technical education often ignore more effective ways of reporting and treating missing data and instead implement traditional, but ineffective, missing data methods (Gemici, Rojewski, & Lee, 2012). The recent methodological, and even the non-methodological, literature has increasingly emphasized the importance of…

A simulation study compared the performance of robust normal theory maximum likelihood (ML) and robust categorical least squares (cat-LS) methodology for estimating confirmatory factor analysis models with ordinal variables. Data were generated from 2 models with 2-7 categories, 4 sample sizes, 2 latent distributions, and 5 patterns of category…

The current main world university rankings broadly group the leading research universities of nations. Australia's Go8 universities are generally within the top 250 ranked universities, with several institutions in the top 50-100 on some measures. This recognition is commendable, however imperfect the individual rankings may be. Use is made of…

Schools and school systems throughout the nation are increasingly experimenting with using various instructional technologies to improve productivity and decrease costs, but evidence on both the effectiveness and the costs of education technology is limited. A recent report published by the Thomas B. Fordham Institute sets out to describe "the…

Among the varied analytical challenges institutional researchers face, examining faculty pay may be one of the most vexing. Although the literature on faculty compensation analysis dates back to the 1970s (Loeb and Ferber, 1971; Gordon, Morton, and Braden, 1974; Scott, 1977; Braskamp and Johnson, 1978; McLaughlin, Smart, and Montgomery, 1978),…

Researchers persist in using stepwise regression in spite of problems with this approach. As noted by B. Thompson (1995), three problems accompany the use of stepwise applications. The first is that computer packages may use incorrect degrees of freedom in their computations, resulting in a greater likelihood of obtaining a spurious statistical…

Nonlinear relationships and latent variable assumptions can lead to serious specification errors in structural models. A quadratic relationship, described by a linear structural model with a latent variable, is shown to have less predictive validity than a simple manifest variable regression model. Advocates the use of simpler preliminary…

Stepwise regression is not an adequate technique to provide the best set of variables with which to predict the dependent variable. By using the stepwise regression method, one who attempts to select the best set of predictors of a given dependent variable will face more problems than he or she attempted to resolve. This is illustrated with an…

The accuracy and variability of 4 cross-validation procedures and 18 formulas were compared concerning their ability to estimate the population multiple correlation and the validity of the sample regression equation in the population. The investigation included two types of regression, multiple and stepwise; three sample sizes, N = 30, 60, 120;…

Assesses the reliability and stability of television exposure, and the relationship of various demographic variables to this hypothetical construct, when measurement error is removed. Analyzes data collected from Black adults. Concludes that more attention should be given to theoretically defining media exposure and to taking into account…

Structural equation models merge multiple regression, path analysis, and factor analysis techniques into a single data analytic framework. Measurement models are developed to define latent variables, and structural equations are then established among the latent variables. Explains the development of these models. (KS)

Examined methodological issues related to the detection and evaluation of behavioral toxicity in infants and children, focusing on the selection of appropriate variables and strategies to control for confounding, sampling strategies and the problem of "overcontrol" for confounding; and the evaluation of dose-response relations and…

Drawing from work on the meta-analysis of over 500 validation studies of the General Aptitude Test Battery (GATB) by the U.S. Employment Service, the paper presents a methodological message and a substantive message. Gene Glass's methods, as used by Edwin Ghiselli in personnel selection, ignore study artifacts (sampling error, error of…