[R] Wilks Lamba

[Peter Dalgaard BSA]

Sven Garbade <garbade at psy.uni-muenchen.de> writes:

> Hi all,
> 
> I can't figure out how to compute Wilks Lambda in a one way repeated
> measure design. My matrix looks like:
> 
> > t2.m
>   Blank   ECR   ENC   UEA   UED
> 1 -0.15  0.14  0.16  0.09  0.14
> 2  0.30  0.08  0.14  0.14  0.14
> [...]
> 
> where each row is a case and the columns are levels of one factor (named
> trial):
> 
> > t2.fit <- manova(t2.m ~ 1)
> > summary(t2.fit, intercept=T, test="Wilks")
>             Df   Wilks approx F num Df den Df Pr(>F)
> (Intercept)  1 0.26869  1.63302      5      3 0.3642
> Residuals    7
> 
> ist this correct? I ask because SPSS gives me a different result:
> 
> Effect: Trial
> Wilks:    0.392
> F:        1.554
> Df:       4
> error Df: 4
> Pr:       0.340
> 
> Thanks for any hints, Sven

Hmm. The ways of SPSS are sometimes mysterious, but the Df suggest
that you're testing that the 5 variables all have mean zero, whereas
SPSS might be testing whether they have the *same* mean. You can check
that by looking at

t2.m2 <- t2.m[,-1] -  t2.m[,1]
t2.fit <- manova(t2.m ~ 1)

-- 
   O__  ---- Peter Dalgaard             Blegdamsvej 3  
  c/ /'_ --- Dept. of Biostatistics     2200 Cph. N   
 (*) \(*) -- University of Copenhagen   Denmark      Ph: (+45) 35327918
~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk)             FAX: (+45) 35327907
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