Hi,
i was working with this model
> mq<-glm(rojos~edadysexo*zona*estacion,quasipoisson)
and i get this minimal adequate model
> anova(mq5,test="F")
Df Deviance Resid. Df Resid. Dev F Pr(>F)
NULL 518 64799
edadysexo 2 1556.5 516 63243 8.9434 0.0001524 ***
zona 4 13590.6 512 49652 39.0448 < 2.2e-16 ***
estacion 1 10069.1 511 39583 115.7112 < 2.2e-16 ***
zona:estacion 4 2879.6 507 36704 8.2728 1.809e-06 ***
I know the correct syntaxis to make a post-hoc comparisonfor single factor
> summary(glht(mq5, linfct=mcp(edadysexo="Tukey")))
Estimate Std. Error z value Pr(>|z|)
M - H == 0 0.28976 0.09541 3.037 0.0060 **
SUB - H == 0 -0.22610 0.22626 -0.999 0.5609
SUB - M == 0 -0.51586 0.21921 -2.353 0.0441 *
(Adjusted p values reported -- single-step method)
and with a single factor involved in an interaction
> summary(glht(mq5, linfct=mcp(estacion="Tukey",
interaction_average=TRUE)))
Estimate Std. Error z value Pr(>|z|)
verano - primavera == 0 -1.352 0.151 -8.952 <2e-16 ***
(Adjusted p values reported -- single-step method)
But how can i test the interaction "zona:estacion", I've tried to
do this
ways, but doesn't work
1. > summary(glht(mq5, linfct=mcp((estacion:zona)="Tukey",
interaction_average=TRUE)))
2.> s<-interaction(zona,estacion)> mqs<-glm(rojos~edadysexo+zona+estacion+s,quasipoisson)
> summary(glht(mqs, linfct=mcp(s="Tukey")))
Error en modelparm.default(model, ...) :
dimensions of coefficients and covariance matrix don't match
Anyone can helps?
-----
Mario Garrido Escudero
PhD student
Dpto. de Biolog?a Animal, Ecolog?a, Parasitolog?a, Edafolog?a y Qca. Agr?cola
Universidad de Salamanca
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