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 UED1 -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)summary(t2.fit, intercept=T, test="Wilks")

(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

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