Life Satisfaction with Imputed Data

Loading the dataset

data.test4 <- read.csv("/Volumes/TOSHIBA EXT/Dropbox/ADULT STUDY/adult_study011615.csv")

Creating a new variable that is the mean of all LIFE SATISFACTION questions

data.test4$LS <- apply(data.test4[, c("LS1","LS2", "LS3", "LS4",  "LS5")], 1, mean, na.rm = TRUE)

Loading packedges

library(reshape2); library(car); library(Amelia);library(mitools);library(nlme)

## Loading required package: Rcpp
## ## 
## ## Amelia II: Multiple Imputation
## ## (Version 1.7.3, built: 2014-11-14)
## ## Copyright (C) 2005-2015 James Honaker, Gary King and Matthew Blackwell
## ## Refer to http://gking.harvard.edu/amelia/ for more information
## ##

Reseting dataset into long version

data <- data.test4[,c("ID", "GROUP", "wave", "LS")]
data <- dcast(data, ID + GROUP ~ wave, mean, value.var = "LS")
data[,3:5] <- apply(data[,3:5],2,function(x) recode(x, "NaN = NA") )
data2 <- as.data.frame(mapply(c,data[,1:4], data[,c(1:3,5)]))
data2$wave <- rep(1:2, each=89)
names(data2) <- c("ID", "GROUP", "BASELINE", "LS", "WAVE")

Imputing missing data

MI <- amelia(data2, 5, idvars = c("GROUP","ID","WAVE"))

## -- Imputation 1 --
## 
##   1  2  3  4  5  6  7
## 
## -- Imputation 2 --
## 
##   1  2  3  4  5  6
## 
## -- Imputation 3 --
## 
##   1  2  3  4  5  6  7  8  9
## 
## -- Imputation 4 --
## 
##   1  2  3  4  5  6  7
## 
## -- Imputation 5 --
## 
##   1  2  3  4  5  6

Creating new dataset with missing data imputed

data(MI$imputations)

## Warning in data(MI$imputations): data set 'MI$imputations' not found

LSwIM<-lapply(MI$imputations,function(X) {lme(LS ~ GROUP * WAVE + BASELINE, random = ~1 | ID, data = X, method = "ML")})
betas<-MIextract(LSwIM, fun=fixef)
vars<-MIextract(LSwIM, fun=vcov)
summary(MIcombine(betas,vars))

## Multiple imputation results:
##       MIcombine.default(betas, vars)
##                results         se     (lower    upper) missInfo
## (Intercept)  1.8434723 0.43659597  0.9728309 2.7141138     26 %
## GROUP        0.4269963 0.52613148 -0.7043993 1.5583920     60 %
## WAVE         0.0703646 0.22074828 -0.3784065 0.5191357     38 %
## BASELINE     0.6140755 0.09532083  0.3998714 0.8282796     71 %
## GROUP:WAVE  -0.1520858 0.29421662 -0.7635046 0.4593331     48 %