VIM (version 4.3.0)

regressionImp: Regression Imputation

Description

Impute missing values based on a regression model.

Usage

regressionImp(formula, data, family = "AUTO", robust = FALSE,
  imp_var = TRUE, imp_suffix = "imp", mod_cat = FALSE)

Arguments

formula

model formula to impute one variable

data

A data.frame or survey object containing the data

family

family argument for "glm" ("AUTO" tries to choose automatically, only really tested option!!!)

robust

TRUE/FALSE if robust regression should be used

imp_var

TRUE/FALSE if a TRUE/FALSE variables for each imputed variable should be created show the imputation status

imp_suffix

suffix used for TF imputation variables

mod_cat

TRUE/FALSE if TRUE for categorical variables the level with the highest prediction probability is selected, otherwise it is sampled according to the probabilities.

Value

• the imputed data set.

Details

"lm" is used for family "normal" and glm for all other families. (Robust=TRUE: lmrob, glmrob)

Examples

data(sleep)
sleepImp1 <- regressionImp(Dream+NonD~BodyWgt+BrainWgt,data=sleep)
sleepImp2 <- regressionImp(Sleep+Gest+Span+Dream+NonD~BodyWgt+BrainWgt,data=sleep)

data(testdata)
imp_testdata1 <- regressionImp(b1+b2~x1+x2,data=testdata$wna)
imp_testdata3 <- regressionImp(x1~x2,data=testdata$wna,robust=TRUE)