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about me statistics example data twitter-mining (german) raspberry pi (german) links Datenschutz analysis, visualisation and playing around with data Multiple Imputation in R. How to impute data with MICE for lavaan. 2017-01-14 by Niels Missing data is unavoidable in most empirical work. This can be a problem for any statistical analysis that needs data to be complete. Structural equation modeling and confirmatory factor analysis are such methods that rely on a complete dataset. The following post will give an overview on the background of missing data analysis, how the missingness can be investigated, how the R-package MICE for multiple imputation is applied and how imputed data can be given to the lavaan-package for confirmatory factor analysis. If you are in a hurry and already know the background of multiple imputation, jump to: How to use multiple imputation with lavaan What kinds of missing data are there? There are two types of missingness: Unit nonresponse concerns cases in

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