… analysis, several studies have shown that it is particularly important for the imputation
model to take the multilevel structure into account if analyses based on the imputed data are to …

… Under the structural equation modeling (SEM) framework, a better approach that takes into
… deletion and multiple imputation in the context of ordinal factor analysis models with missing …

… methods such as multiple imputation. This is particularly true when subsequent analyses
are complex (eg, a hierarchical structural equation model with a complex latent measurement …

… to outline a novel multiple imputation approach to multilevel … models with random intercepts),
classic multiple imputation … normal variables in structural equation modeling software such …

… analysis, it is clear that using the total N under FIML will produce values of \( {R}_{Adj}^2 \)
equivalent to those that would be obtained under the same model using multiple imputation. …

… multiple imputation to impute missing values when the substantive analysis is a weighted
model. … which define level-two, (ii) we include random intercepts, and (iii) we allow the variance …

… imputation models to parametric imputation models in MICE by specifying a compatible
parametric imputation model as … We compare performance of the MICE imputation methods via …

… incorporated into the imputation regression model through a … 10 called this strategy multiple
imputation with missing … general strategy “sequential regression multiple imputation with …

… the strengths of meta-analysis and structural equation modeling. Meta-analysis is useful in …
, whereas structural equation modeling allows researchers to test different theoretical models. …

… Chapter 12 is also a new contribution with Whitney Moore where we discuss various finite
mixture models (eg, latent profile/class models) to look for unknown heterogeneity (ie, unique …