Dear R help group, I am teaching myself linear mixed models with missing data
since I would like to analyze a stats design with these kind of models. The
textbook example is for the procedure "proc MIXED" in SAS, but I would like to
know if there is an equivalent in R. This example only includes two
time-measurements across subjects (a t-test "with missing values"), but I will
need to to this with three time-measurements (repeated measures ANOVA with
missing values):
Patient Treatment
A B
1 20 12
2 26 24
3 16 17
4 29 21
5 22 N/A
6 N/A 12
I have tried this analysis using using the instructions below with the help of
"Mixed-Effects Models in S and S-Plus", but have not been able to go around the
missing data issue as follows:
tmtA <- c(20,26, 16,29,22,NA)
tmtB <- c(12,24,17,21,NA,17)
require(lme4)
dv <- c(20,12,26,24,16,17,29,21,22,17)
subject <- rep(c("s1","s2","s3","s4","s5","s6"),each=2)
subject <- subject[-c(10,11)]
myfactor <- rep(c("f1","f2"), 6)
myfactor <- myfactor[-c(10,11)]
mydata <- data.frame(dv, subject, myfactor)
am2 <- lmer(dv ~ myfactor + (1|subject)), data = mydata)
summary(am2)
anova(am2)
subject <- subject[-c(10,11)]
Any help would be greatly appreciated. Thank you,
Rafael Diaz
Assistant Professor
Math and Stats Dept
California State University Sacramento
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