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multiple comparisons for lme using multcomp
2 messages · Michaël, Peter Dalgaard
Micha?l Coeurdassier <michael.coeurdassier at univ-fcomte.fr> 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 ~~~~~~~~~~ - (p.dalgaard at biostat.ku.dk) FAX: (+45) 35327907