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mi (version 0.06-5)

Missing Data Imputation and Model Checking

Description

Missing-data imputation and model checking

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Version

Install

install.packages('mi')

Monthly Downloads

25,787

Version

0.06-5

License

GPL (>= 2)

Maintainer

YuSung Su

Last Published

April 23rd, 2009

Functions in mi (0.06-5)

mi.info

Function to create information matrix for missing data imputation
mi.method

Virtual class for all mi classes.
mi.count

Elementary function: Bayesian overdispersed poisson regression to impute a count variable.
mi.polr

Elementary function: multinomial log-linear models to impute a ordered categorical variable.
mi.scatterplot

Multiple Imputation Scatterplot
CHAIN

Subset of variables from the CHAIN project, a longitudinal cohort study of people living with HIV in New York City.
plot.mi

Diagnostic Plots for multiple imputation object
mi.dichotomous

Elementary function: Bayesian logistic regression to impute a dichotomous variable.
mi.completed

Multiply Imputed Dataframes
random.imp

Random Imputation of Missing Data
mi.info.update

function to update mi.info object to use for multiple imputation
missing.pattern.plot

Missing Pattern Plot
type.models

Functions to identify types of the models of the mi object
mi.preprocess

Preproessing and Postprocessing mi data object
prior.control

Auxiliary for Adding Priors to Missing Data Imputation
mi

Multiple Iterative Regression Imputation
mi.hist

Multiple Imputation Histogram
mi.categorical

Elementary function: multinomial log-linear models to impute a categorical variable.
mi.pmm

Elementary function: Probability Mean Matching for imputation.
mi.fixed

Elementary function: imputation of constant variable.
mi.pooled

Modeling Functions for Multiply Imputed Dataset
typecast

Variables type
mi.continuous

Elementary function: linear regression to impute a continuous variable.
convergence.plot

Convergence Plot of mi Object