[R] repeated measures with missing data

ONKELINX, Thierry Thierry.ONKELINX at inbo.be
Mon Jul 5 10:00:23 CEST 2010


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]]
> 
> ______________________________________________
> R-help op r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide 
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
> 

Druk dit bericht a.u.b. niet onnodig af.
Please do not print this message unnecessarily.

Dit bericht en eventuele bijlagen geven enkel de visie van de schrijver weer 
en binden het INBO onder geen enkel beding, zolang dit bericht niet bevestigd is
door een geldig ondertekend document. The views expressed in  this message 
and any annex are purely those of the writer and may not be regarded as stating 
an official position of INBO, as long as the message is not confirmed by a duly 
signed document.



More information about the R-help mailing list