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miceMNAR (version 1.0.2)

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

Description

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).

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Version

Install

install.packages('miceMNAR')

Monthly Downloads

14

Version

1.0.2

License

GPL-2 | GPL-3

Maintainer

Jacques-Emmanuel Galimard

Last Published

August 27th, 2018

Functions in miceMNAR (1.0.2)

MNARargument

generate_JointModelEq

Generation of an empty matrix for sample selection model
mice.impute.heckprob

Imputation by bivariate probit sample selection model for binary Missing Not At Random outcome
miceMNAR-package

miceMNAR
mice.impute.hecknorm

Imputation by Heckman's model for continuous outcome with Missing Not At Random mechanism using one-step estimator
mice.impute.hecknorm2step

Imputation by Heckman's model for continuous Missing Not At Random ouctome using a two-step estimator