[R] repeated measures with missing data

[ONKELINX, Thierry]

Dear Rafael,

The line below had one closing bracket to much. The line below should
work.

am2 <- lmer(dv ~ myfactor + (1|subject), data = mydata)

Furthermore I would advise to change myfactor for a character variable
to a factor.

HTH,

Thierry


------------------------------------------------------------------------
----
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek
team Biometrie & Kwaliteitszorg
Gaverstraat 4
9500 Geraardsbergen
Belgium

Research Institute for Nature and Forest
team Biometrics & Quality Assurance
Gaverstraat 4
9500 Geraardsbergen
Belgium

tel. + 32 54/436 185
Thierry.Onkelinx op inbo.be
www.inbo.be

To call in the statistician after the experiment is done may be no more
than asking him to perform a post-mortem examination: he may be able to
say what the experiment died of.
~ Sir Ronald Aylmer Fisher

The plural of anecdote is not data.
~ Roger Brinner

The combination of some data and an aching desire for an answer does not
ensure that a reasonable answer can be extracted from a given body of
data.
~ John Tukey
  

> -----Oorspronkelijk bericht-----
> Van: r-help-bounces op r-project.org 
> [mailto:r-help-bounces op r-project.org] Namens Rafael Diaz
> Verzonden: maandag 5 juli 2010 3:37
> Aan: r-help op r-project.org
> Onderwerp: [R] repeated measures with missing data
> 
> 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
> 
> 
> 
>       
> 	[[alternative HTML version deleted]]
> 
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