# [R] library(car): Anova and repeated measures without between subjects factors

Ralf Goertz R_Goertz at web.de
Tue Oct 16 17:20:07 CEST 2007

```Hi,

sorry if this is explained somewhere but I didn't find anything.

How can I use "Anova" from the car package to test a modell without
between subject's factors? Suppose I have the following data

mat.1 mat.2 mat.3 di ex
1     85    85    88  1  1
2     90    92    93  1  1
3     97    97    94  1  1
4     80    82    83  1  1
5     91    92    91  1  1
6     83    83    84  2  1
7     87    88    90  2  1
8     92    94    95  2  1
9     97    99    96  2  1
10   100    97   100  2  1
11    86    86    84  1  2
12    93   103   104  1  2
13    90    92    93  1  2
14    95    96   100  1  2
15    89    96    95  1  2
16    84    86    89  2  2
17   103   109    90  2  2
18    92    96   101  2  2
19    97    98   100  2  2
20   102   104   103  2  2
21    93    98   110  1  3
22    98   104   112  1  3
23    98   105    99  1  3
24    87   132   120  1  3
25    94   110   116  1  3
26    95   126   143  2  3
27   100   126   140  2  3
28   103   124   140  2  3
29    94   135   130  2  3
30    99   111   150  2  3

Using

> Anova(lm(mat~di*ex,data=data),idata=data.frame(zeit=ordered(1:3)),idesign=~zeit)

Type II Repeated Measures MANOVA Tests: Pillai test statistic
Df test stat approx F num Df den Df    Pr(>F)
di          1     0.377   14.524      1     24 0.0008483 ***
ex          2     0.800   47.915      2     24 4.166e-09 ***
di:ex       2     0.281    4.695      2     24 0.0190230 *
zeit        1     0.782   41.209      2     23 2.491e-08 ***
di:zeit     1     0.252    3.865      2     23 0.0357258 *
ex:zeit     2     0.836    8.611      4     48 2.538e-05 ***
di:ex:zeit  2     0.518    4.189      4     48 0.0054586 **
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

works as expected. But every once in a while I have a model without
between subject's factors. So I thought of

> Anova(lm(mat~1,data=data),idata=data.frame(zeit=factor(1:3)),idesign=~zeit)
Fehler in L %*% B : nicht passende Argumente

(Error in L %*% B : non matching arguments)

On the other hand using anova.mlm I get

> anova.mlm(lm(mat~1,data),idata=data.frame(zeit=factor(1:3)),X=~1,test="Spherical")
Analysis of Variance Table

Contrasts orthogonal to
~1

Greenhouse-Geisser epsilon: 0.7464
Huynh-Feldt epsilon:        0.7777

Df      F num Df den Df     Pr(>F)     G-G Pr     H-F Pr
(Intercept)  1 11.767      2     58 5.1375e-05 3.1183e-04 2.4939e-04
Residuals   29

How can achieve this with Anova?