Pages that link to "Item:Q1406954"

The following pages link to The comparative efficacy of imputation methods for missing data in structural equation model\-ing. (Q1406954):

Displaying 15 items.

• Missing data imputation through GTM as a mixture of \(t\)-distributions (Q858901) (← links)
• A new approach for data editing and imputation (Q999135) (← links)
• On structural equation modeling with data that are not missing completely at random (Q1092564) (← links)
• Imputing missing values in unevenly spaced clinical time series data to build an effective temporal classification framework (Q1654258) (← links)
• Dealing with missing data based on data envelopment analysis and halo effect (Q1788728) (← links)
• Methods for mediation analysis with missing data (Q1940988) (← links)
• Data generation for composite-based structural equation modeling methods (Q2022482) (← links)
• An evaluation of methods to handle missing data in the context of latent variable interaction analysis: multiple imputation, maximum likelihood, and random forest algorithm (Q2103281) (← links)
• The case for the use of multiple imputation missing data methods in stochastic frontier analysis with illustration using English local highway data (Q2272300) (← links)
• Missing data, imputation, and endogeneity (Q2398607) (← links)
• The evidential reasoning approach for multi-attribute decision analysis under interval uncertainty (Q2503257) (← links)
• Imputation techniques for incomplete data in quadratic discriminant analysis (Q4912061) (← links)
• The Effect of Methods for Handling Missing Values on the Performance of the MEWMA Control Chart (Q4929177) (← links)
• Strategies for handling missing data in longitudinal studies with questionnaires (Q4960771) (← links)
• Multiple imputation of discrete and continuous data by fully conditional specification (Q5425040) (← links)