[R] aov() and lme()

From: Jan Wiener <jan.wiener_at_tuebingen.mpg.de>
Date: Thu 27 Oct 2005 - 21:14:59 EST


Sorry for reposting, but even after extensive search I still did not find any answers.

using:
summary(aov(pointErrorAbs~noOfSegments*turnAngle+Error(subj/(noOfSegments+turnAngle)), data=anovaAllData ))

with subj being a random factor and noOfSegments and turnAngle being fixed factors, I get the following results:



Error: subj

           Df Sum Sq Mean Sq F value Pr(>F) Residuals 17 246606 14506

Error: subj:noOfSegments

              Df Sum Sq Mean Sq F value Pr(>F) noOfSegments 3 7806.6 2602.2 5.3257 0.002864 ** Residuals 51 24919.4 488.6
---

Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Error: subj:turnAngle

           Df Sum Sq Mean Sq F value Pr(>F) turnAngle 5 14660 2932 3.1707 0.01131 * Residuals 85 78600 925
---

Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Error: Within

                         Df Sum Sq Mean Sq F value    Pr(>F)
noOfSegments:turnAngle  15  19637    1309  2.9135 0.0001711 ***
Residuals              687 308687     449

---

Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

all is fine, and I get exactly the same results as with unix anova.

No I trying to fit the same data with lme and using the following call:

anova(lme(fixed=pointErrorAbs~noOfSegments*turnAngle, random=~1|subj, data=anovaAllData))

Unfortunately the results are 'really' different from the aov() procedure (I guess I have the call wrong):


(Intercept)                1   823 42.10888  <.0001
noOfSegments               3   823  5.19549  0.0015
turnAngle                  5   823  5.85379  <.0001
noOfSegments:turnAngle 15 823 2.61373 0.0007

I, however, need a comparable method for lme(), because in a different data set I have single empty cells and can therefore not use aov().

does anyone know how to fit with lme() to obtain the same results (for this balanced data set) as with aov().

Thanks in advance,
Jan



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