Sampling Weights in Latent Variable Modeling

Abstract

This article reviews several basic statistical tools needed for modeling data with sampling weights that are implemented in Mplus Version 3. These tools are illustrated in simulation studies for several latent variable models including factor analysis with continuous and categorical indicators, latent class analysis, and growth models. The pseudomaximum likelihood estimation method is reviewed and illustrated with stratified cluster sampling. Additionally, the weighted least squares method for estimating structural equation models with categorical and continuous outcomes implemented in Mplus extended to incorporate sampling weights is also illustrated. The performance of several chi-square tests under unequal probability sampling is evaluated. Simulation studies compare the methods used in several statistical packages such as Mplus, HLM, SAS Proc Mixed, MLwiN, and the weighted sample statistics method used in other software packages.

Fitting Log-Linear Models to Contingency Tables From Surveys With Complex Sampling Designs: An Investigation of the Clogg-Eliason Approach

“…One advantage of this approach is its generality; it is applicable to a very broad class of complex sampling schemes and to a wide range of statistical modelling methods, especially those based upon generalized linear models but also other methods such as latent variable modelling (Asparouhov, 2005).…”

The Model-Size Effect on Traditional and Modified Tests of Covariance Structures

“…In a recent Monte Carlo investigation, Asparouhov (2005) found the adjusted chi-square statistic to have excellent Type I error rates compared to T ML and T S C . Fouladi (2000) conducted an extensive simulation study with 12 different test statistics and found T AD to outperform all other statistics with respect to Type I error rate "under more general nonnormal distributional conditions" (p. 400; cf.…”

“…Most Monte Carlo studies reported in the literature examined very small population models; see, for example, Asparouhov (2005) and Fouladi (2000). As for the factor models in Hoogland's (1999) meta-analysis, d ranged from 2 to 98.…”

Do they intend to stay? An empirical study of commercial apprentices’ motivation, satisfaction and intention to remain within the learned occupation

“…A distinction is made between the intention to leave a job or profession (i.e., turnover intention) and actual turnover. However, intention is known to be an actively formulated proposition to act and therefore a strong predictor of actual behavior (Ajzen 1991;Heckhausen and Heckhausen 2006). The cognitive process of turnover intention has been empirically confirmed as the most important predictor of realized turnover (i.e., leaving an organization or job), as Rosser (2004) and Coomber and Barriball (2007) have reported.…”

“…It would be interesting to examine how the single dimensions influence the development of the intention to remain. Furthermore, there might be alternative approaches to motivation that may explain more variance in the intention to remain within the occupation, such as the expectancy-value theory of motivation (Wigfield and Eccles 2000), the theory of planned behavior (Ajzen 1991) or the person-fit-theory (Eccles et al 1993;Neuenschwander 2010). In alignment with the theoretical focus on self-determined motivation and interested motivation, an instrument was used that has frequently been implemented in the field of VET research, but its factorial structure could not be replicated in the current study.…”