[S] Analysis of split-plot designs

Laffont, Jean-Louis (Laffont@phibred.com)
Thu, 23 Apr 1998 03:56:32 -0500


Dear S-users,

A couple of days ago, I posted some questions about the analysis of
split-plot designs using S-Plus (specifying the model, analysis when
there are missing values, using lme for the analysis).
As I have received no answer, I send again this message.
Thanks for your help.
Jean-Louis
---------------------
Jean-Louis Laffont
Pioneer Semences
Aussonne - France
email: laffont@phibred.com
---------------------
> I am using S-Plus 4.0, release 3 and I have some questions about
> split-plot analysis.
> I will use data frame oats provided in Venables & Ripley (p.178 -
> table 6.2) to illustrate my questions.
>
> 1. Standard error of differences when specifying the model in
> different ways
>
> Specifying the model as in Venables & Ripley works well for getting
> standard error of differences:
> > oats.aov1<-aov(Y~N*V+Error(B/V),data=oats,qr=T)
> > se.contrast(oats.aov1,list(V=="Victory",V=="Marvellous"))
> [,1]
> [1,] 7.078904
>
> However, specifying the model as below, I get an error message:
> >
> oats.aov2<-aov(Y~B+N*V+Error(paste(B,V)+paste(B,V,N)),data=oats,qr=T)
> > summary(oats.aov2)
> Error: paste(B, V)
> Df Sum of Sq Mean Sq F Value Pr(F)
> B 5 15875.28 3175.056 5.28005 0.0124404
> V 2 1786.36 893.181 1.48534 0.2723869
> Residuals 10 6013.31 601.331
>
> Error: paste(B, V, N)
> Df Sum of Sq Mean Sq F Value Pr(F)
> N 3 20020.50 6673.500 37.68565 0.0000000
> N:V 6 321.75 53.625 0.30282 0.9321988
> Residuals 45 7968.75 177.083
> > se.contrast(oats.aov2,list(V=="Victory",V=="Marvellous"))
> Error in c.qr[e.assign[[strata.nm]], , drop = F]: Array subscript
> (89) out of bounds, should be at most 72
> Dumped
>
> Am I doing something wrong when calling se.contrast?
>
> 2. Anova table when missing data
>
> Suppose I have 1 missing data in oats:
>
> > oats.1NA<-oats[-1,]
> > oats.1NA.aov1<-aov(Y~N*V+Error(B/V),data=oats.1NA,qr=T)
> > summary(oats.1NA.aov1)
> Error: B
> Df Sum of Sq Mean Sq F Value Pr(F)
> N 1 14758.53 14758.53 34.47047 0.004203461
> Residuals 4 1712.60 428.15
>
> Error: V %in% B
> Df Sum of Sq Mean Sq F Value Pr(F)
> N 1 1072.061 1072.061 2.097827 0.1814346
> V 2 2847.696 1423.848 2.786211 0.1143401
> Residuals 9 4599.304 511.034
>
> Error: Within
> Df Sum of Sq Mean Sq F Value Pr(F)
> N 3 18732.82 6244.275 34.71880 0.0000000
> N:V 6 299.32 49.886 0.27737 0.9446197
> Residuals 44 7913.52 179.853
>
> As I am not familiar with split-plot analysis with missing data, could
> anyone confirm me this sum of squares partitioning for the whole-plot
> analysis?
>
> 3. Analysis using lme
>
> I tried to use lme for the analysis following "Complements to Modern
> Applied Statistics with S+ - Venables & Ripley" that is:
>
> > oats$sp<-model.matrix(~V-1,oats)
> > options(contrasts=c("contr.treatment","contr.poly"))
> >
> oats.lme<-lme(Y~N*V,random=~sp,cluster=~B,data=oats,re.block=list(1,2:
> 4),
> re.structure=c("unrestricted","identity"),
> control=lme.control(tol=1e-10,ms.tol=1e-10))
> > summary(oats.lme)
> .....
> Fixed Effects Estimate(s):
> Value Approx. Std.Error z ratio(C)
> (Intercept) 80.0000000 9.106976 8.7844743
> N0.2cwt 18.5000000 7.682954 2.4079280
> N0.4cwt 34.6666667 7.682954 4.5121533
> N0.6cwt 44.8333333 7.682954 5.8354291
> VMarvellous 6.6666667 9.715025 0.6862223
> VVictory -8.5000000 9.715025 -0.8749334
> ......
> The standard errors for variety differences don't agree with what I
> get in 1 (that is 7.078904).
> What am I doing wrong in writting the model and is it possible to have
> some clarifications about the argument re.block?
>
> Thanks in advance,
> Jean-Louis
> ---------------------
> Jean-Louis Laffont
> Pioneer Semences
> Aussonne - France
> email: laffont@phibred.com
>
>
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