Michaël Coeurdassier <[EMAIL PROTECTED]> writes:
> summary(csimtest(vect,vcov(lm1),cmatrix=contrMat(table(treatment),type="Tukey"),df=59))
....
> Coefficients:
> Estimate t value Std.Err. p raw p Bonf p adj
> Al800-Al100 -2.253 -10.467 0.213 0.000 0.000 0.000
> Al600-Al100 -2.185 -10.389 0.207 0.000 0.000 0.000
> Al400-Al100 -2.036 -9.850 0.210 0.000 0.000 0.000
> Al200-Al100 -1.712 -8.051 0.215 0.000 0.000 0.000
> control-Al100 -1.487 -7.243 0.205 0.000 0.000 0.000
> control-Al800 0.767 -5.282 0.143 0.000 0.000 0.000
> control-Al600 0.698 -5.072 0.148 0.000 0.000 0.000
> control-Al400 0.550 -4.160 0.155 0.000 0.001 0.001
> Al800-Al200 -0.542 -3.488 0.141 0.001 0.006 0.006
> Al600-Al200 -0.473 -3.191 0.140 0.002 0.014 0.012
> Al400-Al200 -0.325 -2.267 0.147 0.027 0.135 0.110
> control-Al200 0.225 -1.593 0.132 0.116 0.466 0.341
> Al800-Al400 -0.217 -1.475 0.152 0.145 0.466 0.341
> Al600-Al400 -0.149 -1.064 0.138 0.292 0.583 0.466
> Al800-Al600 -0.068 -0.449 0.145 0.655 0.655 0.655
>
> > #a friend told me that it is possible to do multiple comparisons for lme
> in a simplest way, i.e. :
> > anova(lm1,L=c("treatmentcontrol"=1,"treatmentAl200"=-1))
> F-test for linear combination(s)
> treatmentAl200 treatmentcontrol
> -1 1
> numDF denDF F-value p-value
> 1 1 12 2.538813 0.1371
>
> > anova(lm1,L=c("treatmentcontrol"=1,"treatmentAl400"=-1))
> F-test for linear combination(s)
> treatmentAl400 treatmentcontrol
> -1 1
> numDF denDF F-value p-value
> 1 1 12 17.30181 0.0013
>
> > anova(lm1,L=c("treatmentcontrol"=1,"treatmentAl600"=-1))
> F-test for linear combination(s)
> treatmentAl600 treatmentcontrol
> -1 1
> numDF denDF F-value p-value
> 1 1 12 25.72466 3e-04
>
> > anova(lm1,L=c("treatmentcontrol"=1,"treatmentAl800"=-1))
> F-test for linear combination(s)
> treatmentAl800 treatmentcontrol
> -1 1
> numDF denDF F-value p-value
> 1 1 12 27.9043 2e-04
>
> > # however, p values are different that those obtained above. Is this way
> OK or not?
Notice that in all cases, the F-value is exactly the square of the
t-value from Csimtest. The main difference is that you have claimed
that the vcov matrix has 59 DF, whereas the lme analysis says 12. I'd
suspect the latter to be (more) correct. Apart from that, notice that
the "L" approach at best gives you the "p raw" value, i.e., it is
uncorrected for multiple testing.
--
O__ ---- Peter Dalgaard Blegdamsvej 3
c/ /'_ --- Dept. of Biostatistics 2200 Cph. N
(*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918
~~~~~~~~~~ - ([EMAIL PROTECTED]) FAX: (+45) 35327907
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