How to do the SEM fit and modification?
SEM Fit and Modification PSY 597 Week 8 Michael Hallquist 12 Oct 2017 1Global fit 1.1Matrix expression of CFA 1.2Model chi-square goodness of fit 1.2.1Assumptions of chi-square test 1.2.2Relationship to likelihood ratio test (LRT) 1.2.3Comparing candidate models against a saturated model 1.2.4Challenges of using the model chi-square test
How are comparative fit indices used in SEM?
Comparative fit indices compare a candidate model (specified by you) against a baselinemodel, which is a minimal model containing only variancesfor observed endogenous variables, but not covariances among them. Thus, the baseline model represents the view that there are no meaningful relationships among variables.
What are measures of global fit in SEM?
Measures of global fit in SEM provide information about how well the model fits the data. Importantly, these statistics attempt to quantify the overall recovery of the observed data without typically considering specific components of fit or misfit in each element of the mean and covariance structure.
When to use Bic to compare estimated models?
It is important to keep in mind that the BIC can be used to compare estimated models only when the numerical values of the dependent variable are identical for all models being compared. The models being compared need not be nested, unlike the case when models are being compared using an F-test or a likelihood ratio test.
What’s the difference between path analysis and Sem?
The main difference between the two types of models is that path analysis assumes that all variables are measured without error. SEM uses latent variables to account for measurement error. A latent variable is a hypothetical construct that is invoked to explain observed covariation in behavior.
What is the function of absolute indices in SEM?
Absolute indices are often a function of the test statistic \\(T\\), which quantifies global fit to the population covariance structure (see model chi-square goodness of fit below). Absolute fit indices can also be a function of the model residuals.