[R] Contrast testing with lme
Gang Chen
gangchen at mail.nih.gov
Tue Aug 7 16:37:11 CEST 2007
I'm trying to run a contrast with lme, but could not get it work:
> anova(lme(Beta ~ Trust*Sex*Freq, random = ~1|Subj, Model), L=c
("TrustT:Sex:Freq"=1, "TrustU:Sex:Freq"=-1))
Error in anova.lme(lme(Beta ~ Trust * Sex * Freq, random = ~1 | Subj, :
Effects TrustT:Sex:Freq, TrustU:Sex:Freq not matched
What is missing? Here is more information:
> summary(lme(Beta ~ Trust*Sex*Freq, random = ~1|Subj, Model))
Linear mixed-effects model fit by REML
Data: Model
AIC BIC logLik
-825.4663 -791.4348 426.7331
Random effects:
Formula: ~1 | Subj
(Intercept) Residual
StdDev: 0.001144573 0.001167392
Fixed effects: Beta ~ Trust * Sex * Freq
Value Std.Error DF t-value p-value
(Intercept) 0.0001090007 0.0005780194 77 0.1885762 0.8509
TrustU 0.0014426378 0.0005836959 77 2.4715572 0.0157
SexM 0.0008230359 0.0005836959 77 1.4100423 0.1626
FreqLo 0.0001998191 0.0005836959 77 0.3423343 0.7330
FreqNo 0.0004900107 0.0005836959 77 0.8394965 0.4038
TrustU:SexM -0.0012598266 0.0008254707 77 -1.5261918 0.1311
TrustU:FreqLo -0.0012383346 0.0008254707 77 -1.5001558 0.1377
TrustU:FreqNo -0.0009141543 0.0008254707 77 -1.1074341 0.2716
SexM:FreqLo -0.0008469211 0.0008254707 77 -1.0259857 0.3081
SexM:FreqNo 0.0006361012 0.0008254707 77 0.7705922 0.4433
TrustU:SexM:FreqLo 0.0013272173 0.0011673918 77 1.1369082 0.2591
TrustU:SexM:FreqNo 0.0006241524 0.0011673918 77 0.5346555 0.5944
...
> anova(lme(Beta ~ Trust*Sex*Freq, random = ~1|Subj, Model))
numDF denDF F-value p-value
(Intercept) 1 77 4.813938 0.0312
Trust 1 77 3.113293 0.0816
Sex 1 77 3.535774 0.0638
Freq 2 77 6.083832 0.0035
Trust:Sex 1 77 1.634858 0.2049
Trust:Freq 2 77 0.678558 0.5104
Sex:Freq 2 77 2.165059 0.1217
Trust:Sex:Freq 2 77 0.647042 0.5264
Thanks,
Gang
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