[R] how to successfully remove missing values for a repeated measures analysis

[Bob Green]

Hello ,

I am hoping for some advice. I want to run a repeated measures ANOVA. The 
primary problem is that my attempt to remove missing values created a 
dataset of missing values.

The data set consists of 92 rows (1 row per participant) x 186 variables.

The steps of the analysis undertaken are outlined below (#). Any assistance 
is appreciated in relation to how to remove the missing values so the 
analysis is run. Feedback regarding the prior steps is also welcomed .

Bob Green



#Step 1

study1dat <- read.csv("c:\\study1.csv",header=T)
attach (study1dat)

outcome <- c(t1frq, t2frq,t3frq,t4frq)
grp <- factor( rep(group, 2,length=368) )
time <- gl(4,92,length=368)
subject <- gl(92,1,length=368)
data.frame(subject, grp, time, outcome)

# there are 3 missing values in $outcome

#Step 2 - create a new data frame removing missing values from variable 
$outcome

  d2<-study1dat[!is.na(outcome),]

#the previous step generates NA values.

#Step 3 detach original data set & attach dataset without missing values
detach(study1dat)

attach(d2)

The following object(s) are masked _by_ .GlobalEnv :         time
         The following object(s) are masked from package:datasets 
:         sleep

#Step 4 run analysis

library(nlme)
anova(lme(outcome ~ grp * time, random = ~ 1 | subject))

#The data is the format below

     subject grp time outcome
1         1   0    1       4
2         2   0    1       3
3         3   0    1       7
4         4   0    1       0
5         5   0    1       1
6         6   0    1       7
7         7   0    1       7
8         8   0    1       7
9         9   0    1       7
10       10 0    1      5