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 at 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 at r-project.org
> [mailto:r-help-bounces at r-project.org] Namens Rafael Diaz
> Verzonden: maandag 5 juli 2010 3:37
> Aan: r-help at 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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>
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