This study proposes a two-stage causal modeling with instrumental variables to mitigate selection bias, provide correct standard error estimates, and address nonnormal and missing data issues simultaneously. Bayesian methods are used for model estimation. Robust methods with Student's "t" distributions are used to account for nonnormal…

Growing scholarship on the pedagogical applications of statistical modeling is currently taking place to create adaptations of this practice to introduce novices to statistics. These are intended to promote novices' reasoning, and are typically void of formal mathematical procedures and calculations. In this article, we define the potential…

In this article, we systematically introduce the just another Gibbs sampler (JAGS) software program to fit common Bayesian cognitive diagnosis models (CDMs) including the deterministic inputs, noisy "and" gate model; the deterministic inputs, noisy "or" gate model; the linear logistic model; the reduced reparameterized unified…

Financial software offers an appealing substitute for an investment in complex financial knowledge to help individuals make better financial decisions. Little is known, however, about which consumers use financial software and whether the use of financial software results in improved financial outcomes. Using data from the 2008 National…

Newer statistical procedures are typically introduced to help address the limitations of those already in practice or to deal with emerging research needs. Quantile regression (QR) is introduced in this paper as a relatively new methodology, which is intended to overcome some of the limitations of least squares mean regression (LMR). QR is more…

The purpose of this research study was to examine the unknown fears of embracing cloud computing which stretches across measurements like fear of change from leaders and the complexity of the technology in 9-1-1 dispatch centers in USA. The problem that was addressed in the study was that many 9-1-1 dispatch centers in USA are still using old…

Prior research studies associated the employment of part-time faculty with student degree and/or certificate completion (Benjamin, 2002; Ehrenberg & Zhang, 2005; Jacoby, 2006; Leslie & Gappa, 2002; Umbach, 2008; Umbach & Wawrzynski, 2005). To date, institutional-level data have been utilized to investigate whether such employment…

Researchers in psychology are increasingly using model selection strategies to decide among competing models, rather than evaluating the fit of a given model in isolation. However, such interest in model selection outpaces an awareness that one or a few cases can have disproportionate impact on the model ranking. Though case influence on the fit…

Longitudinal data describe developmental patterns and enable predictions of individual changes beyond sampled time points. Major methodological issues in longitudinal data include modeling random effects, subject effects, growth curve parameters, and autoregressive residuals. This study embedded the longitudinal model within a multigroup…

This article shows how nonlinear latent curve models may be fitted for simultaneous analysis of multiple variables measured longitudinally using Mx statistical software. Longitudinal studies often involve observation of several variables across time with interest in the associations between change characteristics of different variables measured…

Bayesian and classical approaches to classification of vocational data were compared using an educational data set from a longitudinal study of professional growth and development in organizations (P. Ruohotie et al., 1994). Data were from 2,430 workers in companies in Finland who completed a questionnaire with behavior and background statements.…

The nonlinear random coefficient model has become increasingly popular as a method for describing individual differences in longitudinal research. Although promising, the nonlinear model it is not utilized as often as it might be because software options are still somewhat limited. In this article we show that a specialized version of the model…

A component analytic method for analyzing multivariate longitudinal data is presented that does not make strong assumptions about the structure of the data. Central to the method are the facts that components are derived as linear composites of the observed or manifest variables and that the components must provide an adequate representation of…

In this longitudinal study, relationships were examined between educational aspirations and educational attainment for Australian young adults from different ethnic and social status backgrounds. Participants included 6,811 (3,547 women and 3,264 men) young adults (mean age = 20.3 years) who were in Year 9 when the study began. In the analysis,…

Based on annual reports from the states on project activities carried out under the Library Services and Construction Act (LSCA), this report provides an overview of programs authorized under Title I of LSCA over a 5-year period to support special projects at major urban resource libraries (MURLs) which operated for users on a regional basis. It…