popmis

Hox pupil popularity data with some missing popularity scores

datasets

Multiple imputation using Fully Conditional Specification (FCS)
    implemented by the MICE algorithm. Each variable has its own imputation
    model. Built-in imputation models are provided for continuous data
    (predictive mean matching, normal), binary data (logistic regression),
    unordered categorical data (polytomous logistic regression) and ordered
    categorical data (proportional odds). MICE can also impute continuous
    two-level data (normal model, pan, second-level variables). Passive
    imputation can be used to maintain consistency between variables. Various
    diagnostic plots are available to inspect the quality of the imputations.

Stef van Buuren

mice

Multivariate Imputation by Chained Equations

popmis function

Hox, J. J. (2002) <em>Multilevel analysis. Techniques and
applications.</em> Mahwah, NJ: Lawrence Erlbaum.

popmis: Hox pupil popularity data with missing popularity scores

Description

Arguments

source

Details

Examples