search for: missmda

Hello, I've been working with categorical, binary data and have been using a combination of both FactoMiner and missMDA to impute the binary data set. I have had success imputing the data set and I am now working with a complete set. Now, I wish to reduce the dimensionality of the data and do so using a method similar to logistic or binary PCA. I've been trying to use MCA to accomplish this, but am unsure how...

Dear R users and developers, I have a dataset containing 34 variables measured in a survey, which has some missing items. I would like to conduct a factor analysis of this data. I tested mi, Amelia, and MissForest as alternative packages in order to impute the missing data. I now have 5 separate datasets with the variables I am interested in factor analysing. In my reading of the package

...nction * micEconSNQP (0.6-2) Arne Henningsen http://crantastic.org/packages/micEconSNQP Production analysis with the Symmetric Normalized Quadratic (SNQ) profit function * migui (0.00-08) Yu-Sung Su http://crantastic.org/packages/migui Graphical User Interface of the mi Package * missMDA (1.0) Francois Husson http://crantastic.org/packages/missMDA Imputation of incomplete continuous or categorical datasets; Missing values are imputed with a principal component analysis (PCA) or a multiple correspondence analysis (MCA) model; Perform multiple imputation with and in PCA...