long2mids

ifdo

appendbreak

extractBS

cond

action

data

warp.model

Auxiliary function that are not (yet) part of <code>mice</code>, but that are needed to execute the code for the 
book Flexible Imputation of Missing Data (FIMD).

internal

mice.auxiliary

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.

mice.auxiliary: Auxiliary functions used in FIMD

Description

Usage

Arguments