miceMNAR (1.0.2)

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Missing not at Random Imputation Models for Multiple Imputation by Chained Equation.


Provides imputation models and functions for binary or continuous Missing Not At Random (MNAR) outcomes through the use of the 'mice' package. The mice.impute.hecknorm() function provides imputation model for continuous outcome based on Heckman's model also named sample selection model as described in Galimard et al (2018) and Galimard et al (2016) . The mice.impute.heckprob() function provides imputation model for binary outcome based on bivariate probit model as described in Galimard et al (2018).

Maintainer: Jacques-Emmanuel Galimard
Author(s): Jacques-Emmanuel Galimard [aut, cre] (INSERM, U1153, ECSTRA team), Matthieu Resche-Rigon [aut] (INSERM, U1153, ECSTRA team)

License: GPL-2 | GPL-3

Uses: GJRM, mice, mvtnorm, pbivnorm, sampleSelection

Released over 1 year ago.

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Related packages: Amelia, CVThresh, HardyWeinberg, Hmisc, ade4, cat, eigenmodel, experiment, ltm, memisc, mice, mitools, mix, norm, pan, randomForest, sbgcop, yaImpute, zoo, SNPassoc(20 best matches, based on common tags.)

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