Multilevel structural equation (MSEM) models allow researchers to model latent factor structures at multiple levels simultaneously by decomposing within- and between-group variation. Yet the extent to which the sampling ratio (i.e., proportion of cases sampled from each group) influences the results of MSEM models remains unknown. This paper…

Whether selection processes contribute to group-level disparities or merely reflect pre-existing inequalities is an important societal question. In the context of observational data, researchers, concerned about omitted-variable bias, assess selection-contributing inequality via a kitchen-sink approach, comparing selection outcomes of…

A modification of the first stage of the standard procedure for two-stage meta-analytic structural equation modeling for use with large complex datasets is presented. This modification addresses two common problems that arise in such meta-analyses: (a) primary studies that provide multiple measures of the same construct and (b) the correlation…

Structural equation models play an important role in the social sciences. Consequently, there is an increasing use of meta-analytic methods to combine evidence from studies that estimate the parameters of structural equation models. Two approaches are used to combine evidence from structural equation models: A direct approach that combines…

This case study describes a program of research that developed a new measure--the Adaptability Scale--and then tested this new measure through a set of substantive research questions and publications. Three phases of this research program are detailed: a measurement phase, a modeling phase, and a mediation phase. The aim of this case study is to…

It is now possible to create flexible learning environments without time and distance barriers on the internet. However, research has shown that learners typically experience isolation and alienation in online learning environments. These negative experiences can be reduced by enhancing social presence. In order to better facilitate the perceived…

A readily implemented procedure is discussed for interval estimation of indexes of interrelationship between items from multiple-component measuring instruments as well as between items and total composite scores. The method is applicable with categorical (ordinal) observed variables, and can be widely used in the process of scale construction,…

Recent missing data studies have argued in favor of an "inclusive analytic strategy" that incorporates auxiliary variables into the estimation routine, and Graham (2003) outlined methods for incorporating auxiliary variables into structural equation analyses. In practice, the auxiliary variables often have missing values, so it is reasonable to…

This chapter summarizes ten selected issues and common problems that arise in most assessment research projects. These include: (1) the uses of grades in assessment; (2) institutional review boards; (3) research design as a compromise; (4) standardized testing; (5) self-reported measures; (6) missing data; (7) weighting data; (8) conditional…

The relationship between structural equation modeling (SEM) and canonical correlation analysis (CCA) is illustrated. The representation of CCA in SEM may provide interpretive information not available from conventional CCA. Hierarchically, the relationship suggests that SEM is a more general analytic approach. (SLD)

Seven approaches to averaging reliability coefficients are presented. Each approach starts with a unique definition of the concept of "average," and no approach is more correct than the others. Six of the approaches are applicable to internal consistency coefficients. The seventh approach is specific to alternate-forms coefficients. Although the…

The present study integrates findings from three lines of research on the association of social cognition and externalizing psychopathology, language and externalizing psychopathology, and social cognition and language functioning using Structural Equation Modeling (SEM). To date these associations have been examined in pairs. A sample of 354…

This paper, in a fashion easy to follow, illustrates the interesting relationship between structural equation modeling and canonical correlation analysis. Although computationally somewhat inconvenient, representing canonical correlation as a structural equation model may provide some information which is not available from conventional canonical…

The purposes of this research brief were to examine (a) whether youth reports of neighborhood qualities were significantly related to census data at the block group, measuring the same structural qualities and (b) whether the structural qualities were related to youth development either directly or indirectly through youth perceptions. Data were…

Discusses linear structural relations, Two Stage Least Squares, and path analysis as statistical procedures that sometimes permit causal inferences from correlational findings. Even though two variables cannot be interpreted causally due to a possible but unknown third variable, these methods are appropriate for handling models with correlated…