# Re: [R] Repeated measures

From: Richard Plant <replant_at_ucdavis.edu>
Date: Mon 22 Jan 2007 - 20:17:38 GMT

In the two solutions for the repeated measures problem given in the original reply below, the F and p values given by aov() with the error strata defined by Error() are different from those given by lme(). However, when one does the problem "by hand" using the standard split plot model, the results agree with those of nlme(). The difference between the two aov() solutions is in the partitioning of sums of squares. Is there a ready explanation for this discrepancy?

Thanks,
Richard Plant

> tolerance <- tolerance <-

+
> tolerance.long <- reshape(tolerance,

```+                           varying = list(c("tol11","tol12","tol13",
+                                            "tol14", "tol15")),
+                           v.names = c("tol"), timevar = "time",
+                           times = 11:15, direction = "long")
```

> tolerance.aov2 <- aov(tol ~ factor(male) + factor(male):factor(id) +
factor(time) + factor(time):male, data = tolerance.long)
> tolerance.sum <- summary(tolerance.aov2)
> tolerance.sum
```                        Df Sum Sq Mean Sq F value    Pr(>F)
factor(male)             1 0.3599  0.3599  2.6077  0.111967
factor(time)             4 2.8326  0.7081  5.1309  0.001358 **
factor(male):factor(id) 14 8.2990  0.5928  4.2951 4.295e-05 ***
factor(time):male        4 0.1869  0.0467  0.3386  0.850786
Residuals               56 7.7289  0.1380
```
```---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

> tolerance.list <- tolerance.sum[[1]]
> tolerance.mat <- as.matrix(tolerance.list[3])
> tolerance.F.male <- tolerance.mat[1,1]/tolerance.mat[3,1]

> tolerance.F.male

[1] 0.607137

> tolerance.df <- as.matrix(tolerance.list[1])

> tolerance.p.male <- 1 -

pf(tolerance.F.male,tolerance.df[1,1],tolerance.df[3,1])

> tolerance.p.male

[1] 0.4488394

>
> Message: 68

> Date: Wed, 17 Jan 2007 05:45:01 -0500
> From: Chuck Cleland <ccleland@optonline.net>
> Subject: Re: [R] Repeated measures
> To: Tom Backer Johnsen <backer@psych.uib.no>
> Cc: r-help@stat.math.ethz.ch
> Content-Type: text/plain; charset=ISO-8859-1
>
> Tom Backer Johnsen wrote:
> > I am having a hard time understanding how to perform a "repeated
> > measures" type of ANOVA with R.  When reading the document found
here:

> >
> > http://cran.r-project.org/doc/contrib/Lemon-kickstart/kr_repms.html

> >
> > I find that there is a reference to a function make.rm () that is
> > supposed to rearrange a "one row per person" type of frame to a "one
> > row per observation" type of frame.  But that function does not seem
> > to be there.  Nor does the help.search suggest anything.  Is that
> > function buried in some package?
>
>   I'm not able to find that function.  Perhaps that document is out of
> date.
>
> > Is there  some simple documentation that might be useful somewhere?
> > Starting with a really simple problem (one group, two observations)?
>
>   Here is an example showing the use of reshape() and analysis via
aov()

> and lme() in the nlme package.

>
> tolerance <-
>
tx

> t",

>
> tolerance.long <- reshape(tolerance,
>                           varying = list(c("tol11","tol12","tol13",
>                                            "tol14", "tol15")),
>                           v.names = c("tol"), timevar = "time",
>                           times = 11:15, direction = "long")
>
> tolerance.aov <- aov(tol ~ as.factor(time) * male + Error(id),
>                      data = tolerance.long)
>
> summary(tolerance.aov)
>
> Error: id
>      Df   Sum Sq  Mean Sq
> male  1 0.085168 0.085168
>
> Error: Within
>                      Df  Sum Sq Mean Sq F value  Pr(>F)
> as.factor(time)       4  2.8326  0.7081  3.0538 0.02236 *
> male                  1  0.3024  0.3024  1.3039 0.25745
> as.factor(time):male  4  0.1869  0.0467  0.2015 0.93670
> Residuals            69 16.0002  0.2319
> ---
> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
>
> library(nlme)
>
> tolerance.lme <- lme(tol ~ as.factor(time) * male, random = ~ 1 | id,
>                      data = tolerance.long)
>
> anova(tolerance.lme)
>                      numDF denDF  F-value p-value
> (Intercept)              1    56 353.9049  <.0001
> as.factor(time)          4    56   5.1309  0.0014
> male                     1    14   0.6071  0.4488
> as.factor(time):male     4    56   0.3386  0.8508
>
>   RSiteSearch("repeated measures") points to other examples,
functions,

> and documentation.

>
> > Tom
> >
> > ______________________________________________
> > R-help@stat.math.ethz.ch mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> guide.html
> > and provide commented, minimal, self-contained, reproducible code.
>
> --
> Chuck Cleland, Ph.D.
> NDRI, Inc.
> 71 West 23rd Street, 8th floor
> New York, NY 10010
> tel: (212) 845-4495 (Tu, Th)
> tel: (732) 512-0171 (M, W, F)
> fax: (917) 438-0894
>
>
>
> ------------------------------
>
> _______________________________________________
> R-help@stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

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