I've read something about this problem, but I don't know how can i avoid this problem.

Why the order of the factors give different results? I suppose it's because the order of the factors, i've just changed "lcc" from the first position to the last in the model, and the significance change completely

> modo<-glm(prevalencia~

**lcc**+edadysexo/lcc+edadysexo/mes,binomial)

> anova(modo,test="Chisq")

Df Deviance Resid. Df Resid. Dev P(>|Chi|)

NULL 524 206.97

lcc 1 10.5715 523 196.40 0.001148 **

edadysexo 2 1.0725 521 195.32 0.584929

lcc:edadysexo 2 3.7752 519 191.55 0.151433

edadysexo:mes 9 18.2981 510 173.25 0.031868 *

> mode<-glm(prevalencia~edadysexo/lcc+edadysexo/mes+

**lcc**,binomial)

> anova(mode,test="Chisq")

Df Deviance Resid. Df Resid. Dev P(>|Chi|)

NULL 524 206.97

edadysexo 2 9.9165 522 197.05 0.007025 **

lcc 1 1.7275 521 195.32 0.188732

edadysexo:lcc 2 3.7752 519 191.55 0.151433

edadysexo:mes 9 18.2981 510 173.25 0.031868 *

Ijow can i know what's correct? when i test this two factors separately in a lm (lcc is continuos) and in a chisq.test (edadysexo is categorical) both are significant, and in the model just one of them is significant.

Thanks very much

Mario Garrido Escudero

PhD student

Dpto. de Biología Animal, Ecología, Parasitología, Edafología y Qca. Agrícola

Universidad de Salamanca