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Specification Searches in Multilevel Structural Equation Modeling: A Monte Carlo Investigation
- Source :
-
Structural Equation Modeling: A Multidisciplinary Journal . 2010 17(1):42-65. - Publication Year :
- 2010
-
Abstract
- Cluster sampling results in response variable variation both among respondents (i.e., within-cluster or Level 1) and among clusters (i.e., between-cluster or Level 2). Properly modeling within- and between-cluster variation could be of substantive interest in numerous settings, but applied researchers typically test only within-cluster (i.e., individual difference) theories. Specifying a between-cluster model in the absence of theory requires a specification search in multilevel structural equation modeling. This study examined a variety of within-cluster and between-cluster sample sizes, intraclass correlation coefficients, start models, parameter addition and deletion methods, and Type I error control techniques to identify which combination of start model, parameter addition or deletion method, and Type I error control technique best recovered the population of the between-cluster model. Results indicated that a "saturated" start model, univariate parameter deletion technique, and no Type I error control performed best, but recovered the population between-cluster model in less than 1 in 5 attempts at the largest sample sizes. The accuracy of specification search methods, suggestions for applied researchers, and future research directions are discussed. (Contains 4 tables and 10 figures.)
Details
- Language :
- English
- ISSN :
- 1070-5511
- Volume :
- 17
- Issue :
- 1
- Database :
- ERIC
- Journal :
- Structural Equation Modeling: A Multidisciplinary Journal
- Publication Type :
- Academic Journal
- Accession number :
- EJ879822
- Document Type :
- Journal Articles<br />Reports - Evaluative
- Full Text :
- https://doi.org/10.1080/10705510903438948