> fortune(106)
If the answer is parse() you should usually rethink the question.
-- Thomas Lumley
R-help (February 2005)
Here is one approach that seems to be working:
for (meanCol in paste("Mean_", 1:3, sep="")) {
cat('\n######',meanCol,'\n\n')
f <- formula( paste( meanCol, '~ Group + c1 + c2 + c3' ) )
means.lmeWithCovariate <- lme(f, data=df, random = ~ 1 | Subject)
print(summary(means.lmeWithCovariate))
print(anova(means.lmeWithCovariate))
}
--
Gregory (Greg) L. Snow Ph.D.
Statistical Data Center
Intermountain Healthcare
greg.s...@imail.org
801.408.8111
> -----Original Message-----
> From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-
> project.org] On Behalf Of Connolly, Colm
> Sent: Thursday, August 05, 2010 3:18 PM
> To: r-help@r-project.org
> Subject: [R] eval-parse and lme in a loop
>
> Hi everybody,
>
> I'm having trouble getting an eval-parse combination to work with lme
> in a for loop.
>
> Consider the code below. The call to lme outside the loop works. The
> call to aov inside the loop works, but the call to to lme inside the
> loop does not.
> The latter fails with
>
> Error in model.frame.default(formula = ~meanCol + Group + c1 + c3 +
> Subject, :
> variable lengths differ (found for 'Group')
>
> and I don't know why the eval-parse portion of the code is node being
> replaced as it is in the call to aov. Anybody got any idea what's
> wrong?
>
> rm(list=ls())
>
> library('nlme')
>
> df=data.frame(
> Group=rep(c("ctrl", "short", "long"), each=9, times=1),
> Subject=paste("S", 1:27, sep=""),
> Mean_1=c(-2.335482, 8.269832, 6.704734, -2.355664, 0.724432,
> 11.212987, 5.966652, 10.741065, 3.567522, 5.359832, 4.899951,
> 4.084452, 5.976326, 8.634508, 5.750942, 7.455622, 6.823843,
> 0.903801, 13.198157, 5.238985, 5.171453, 10.273715, 5.184785,
> 6.225874, 8.889997, 12.096968, 9.843028),
> Mean_2=c(16.244444, -1.486571, 1.817303, 3.814328, -0.343775,
> 19.323227, -0.390764, 7.149855, 4.517766, -0.967120, 11.219844,
> 0.561103, 5.188478, -4.819444, 6.253271, 7.062638, 4.502291, -
> 0.469567, 12.739646, 5.832679, 9.193511, 7.664636, 6.083930,
> 9.493136, 7.478424, 7.642287, 7.205822),
> Mean_3=c(7.213662, 2.147219, -1.345795, -0.495567, 3.733844,
> 3.544084, 0.949573, 4.318238, 2.914248, 3.913391, 9.240128,
> 8.315122, 12.323612, 14.622557, 11.169847, 10.857631, 14.637243,
> 7.203096, 7.777472, -1.457673, 2.766380, 9.675148, -5.047292,
> 1.982447, 3.865502, 5.045913, 10.660579),
> c1=rnorm(9, mean=0.1, sd=0.4),
> c2=rnorm(9, mean=0.5, sd=0.7),
> c3=rnorm(9, mean=0.9, sd=1)
> );
>
>
> ## this works
> means.lmeNoCovariate=lme(Mean_1 ~ Group, data=df, random = ~ 1 |
> Subject)
> print(summary(means.lmeNoCovariate))
> print(anova(means.lmeNoCovariate))
>
>
> for (meanCol in paste("Mean_", 1:3, sep="")) {
> ## LMEs go here
>
>
> cat("##################################################################
> ##################################\n")
> cat("### AOV\n")
>
> cat("##################################################################
> ##################################\n")
> ## this works
> means.aov<-aov(eval(parse(text=meanCol)) ~ Group, data=df);
> means.aov.summary=summary(means.aov)
> print(means.aov.summary)
>
>
> cat("##################################################################
> ##################################\n")
> cat("### LME\n")
>
> cat("##################################################################
> ##################################\n")
>
> ## this doe not work
> means.lmeWithCovariate=lme(eval(parse(text=meanCol)) ~ Group + c1 +
> c1 + c3, data=df, random = ~ 1 | Subject)
> print(summary(means.lmeWithCovariate))
> print(anova(means.lmeWithCovariate))
>
> }
>
> Regards,
> --
> Colm G. Connolly, Ph. D.
> Dept of Psychiatry
> University of California, San Diego
> 9500 Gilman Dr. #0738
> La Jolla, CA 92093-0738
> Tel: +1-858-246-0684
>
> ______________________________________________
> R-help@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.
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and provide commented, minimal, self-contained, reproducible code.
