prelim: Converts a dataset imputed by MIMCA, MIPCA or MIFAMD into a...

In missMDA: Handling Missing Values with Multivariate Data Analysis

Converts a dataset imputed by MIMCA, MIPCA or MIFAMD into a mids object

Description

This function performs grouping and sorting operations on a multiply imputed dataset. It creates a mids object that is needed for input to with.mids, which allows analyse of the multiply imputed data set. The original incomplete data set needs to be available so that we know where the missing data are.

Usage

prelim(res.mi,X)

Arguments

res.mi	an output of the functions MIPCA, MIMCA or MIFAMD
X	the original incomplete data set corresponding to the res.mi argument

Value

imp.mids

An object of type mids

Author(s)

Vincent Audigier [e-mail], Francois Husson [e-mail] and Julie Josse [e-mail]

See Also

MIFAMD,MIPCA,MIMCA,with.mids,pool,summary.mira

Examples

## Not run: 
data(TitanicNA)

## First the number of components has to be chosen 
##   (for the reconstruction step)
## nb <- estim_ncpMCA(TitanicNA,ncp.max=5) ## Time-consuming, nb = 5

## Multiple Imputation
res.mi <- MIMCA(TitanicNA, ncp=5, verbose=T)

#Analysis
imp<-prelim(res.mi,TitanicNA)
fit <- with(data=imp,exp=glm(SURV~CLASS+AGE+SEX,family = "binomial"))

#Pooling
res.pool<-pool(fit)
summary(res.pool)

## End(Not run)

missMDA documentation built on Nov. 17, 2023, 5:07 p.m.