> This looks odd. It is a standard split-plot layout, right? 3 > groups of 13 subjects, each measured with two kinds of Rsp = 3x13x2 > = 78 observations.
Yes, that is right. > > In that case you shouldn't see the same effect allocated to > multiple error strata. I suspect you forgot to declare Subj as factor. This is exactly the problem I had: Model$Subj was not a factor! Now they converge. A lesson well learned. Thanks a lot for the help, Gang On Aug 3, 2007, at 4:53 PM, Peter Dalgaard wrote: > Gang Chen wrote: >> Thanks a lot for clarification! I just started to learn >> programming in R for a week, and wanted to try a simple mixed >> design of balanced ANOVA with a between-subject factor >> (Grp) and a within-subject factor (Rsp), but I'm not sure whether >> I'm modeling the data correctly with either of the command lines. >> >> Here is the result. Any help would be highly appreciated. >> >> > fit.lme <- lme(Beta ~ Grp*Rsp, random = ~1|Subj, Model); >> > summary(fit.lme) >> Linear mixed-effects model fit by REML >> Data: Model >> AIC BIC logLik >> 233.732 251.9454 -108.8660 >> >> Random effects: >> Formula: ~1 | Subj >> (Intercept) Residual >> StdDev: 1.800246 0.3779612 >> >> Fixed effects: Beta ~ Grp * Rsp >> Value Std.Error DF t-value p-value >> (Intercept) 1.1551502 0.5101839 36 2.2641837 0.0297 >> GrpB -1.1561248 0.7215090 36 -1.6023706 0.1178 >> GrpC -1.2345321 0.7215090 36 -1.7110417 0.0957 >> RspB -0.0563077 0.1482486 36 -0.3798196 0.7063 >> GrpB:RspB -0.3739339 0.2096551 36 -1.7835665 0.0829 >> GrpC:RspB 0.3452539 0.2096551 36 1.6467705 0.1083 >> Correlation: >> (Intr) GrpB GrpC RspB GrB:RB >> GrpB -0.707 >> GrpC -0.707 0.500 >> RspB -0.145 0.103 0.103 >> GrpB:RspB 0.103 -0.145 -0.073 -0.707 >> GrpC:RspB 0.103 -0.073 -0.145 -0.707 0.500 >> >> Standardized Within-Group Residuals: >> Min Q1 Med Q3 Max >> -1.72266114 -0.41242552 0.02994094 0.41348767 1.72323563 >> >> Number of Observations: 78 >> Number of Groups: 39 >> >> > fit.aov <- aov(Beta ~ Rsp*Grp+Error(Subj/Rsp)+Grp, Model); >> > fit.aov >> >> Call: >> aov(formula = Beta ~ Rsp * Grp + Error(Subj/Rsp) + Grp, data = Model) >> >> Grand Mean: 0.3253307 >> >> Stratum 1: Subj >> >> Terms: >> Grp >> Sum of Squares 5.191404 >> Deg. of Freedom 1 >> >> 1 out of 2 effects not estimable >> Estimated effects are balanced >> >> Stratum 2: Subj:Rsp >> >> Terms: >> Rsp >> Sum of Squares 7.060585e-05 >> Deg. of Freedom 1 >> >> 2 out of 3 effects not estimable >> Estimated effects are balanced >> >> Stratum 3: Within >> >> Terms: >> Rsp Grp Rsp:Grp Residuals >> Sum of Squares 0.33428 36.96518 1.50105 227.49594 >> Deg. of Freedom 1 2 2 70 >> >> Residual standard error: 1.802760 >> Estimated effects may be unbalanced ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.