Hi Ben! Following his recommendations I did the following: 1st step: I compared the best model for binomial and binomial inflates. 1.1 Best model for Binomial.
dg$resp.mumi <- cbind(dg$MUMI,dg$NT - dg$MUMI) dg names(dg) mod.mumi.binomial <- glm(resp.mumi ~ factor(PARTO)*REG, family=binomial, data = dg) summary(mod.mumi.binomial) mod.mumi.binomial1 <- glm(resp.mumi ~ factor(PARTO) + REG, family=binomial, data = dg) summary(mod.mumi.binomial1) mod.mumi.binomial2 <- glm(resp.mumi ~ REG, family=binomial, data = dg) summary(mod.mumi.binomial2) pchisq(-2*(logLik(mod.mumi.binomial1)-logLik(mod.mumi.binomial)),lower.tail=FALSE, df= 15) [1] 0.1354171 pchisq(-2*(logLik(mod.mumi.binomial2)-logLik(mod.mumi.binomial1)),lower.tail=FALSE, df= 5) [1] 0.06030012 The 5% significance level, we can choose the most parsimonious model, ie the model "mod.mumi.binomial2". 1.2 Best model for binomial inflates library(VGAM) mod.mumi.binomialinflacionada <- vglm(resp.mumi ~ factor(PARTO)*REG,zibinomial, data = dg) summary(mod.mumi.binomialinflacionada) mod.mumi.binomialinflacionada1 <- vglm(resp.mumi ~ factor(PARTO)+REG,zibinomial, data = dg) summary(mod.mumi.binomialinflacionada1) mod.mumi.binomialinflacionada2 <- vglm(resp.mumi ~ REG,zibinomial, data = dg) summary(mod.mumi.binomialinflacionada2) pchisq(-2*logLik(mod.mumi.binomialinflacionada1)-logLik(mod.mumi.binomialinflacionada)),lower.tail=FALSE, df= 15) [1] 0.1477837 pchisq(-2*logLik(mod.mumi.binomialinflacionada2)-logLik(mod.mumi.binomialinflacionada1)),lower.tail=FALSE, df= 5) [1] 0.0989934 The 5% significance level, we can choose the most parsimonious model, ie the model "mod.mumi.binomialinflacionada2". 2st step: Compare the best model of the binomial model with the best of inflated binomial. pchisq(-2*(logLik(mod.mumi.binomial2)-logLik(mod.mumi.binomialinflacionada2)),lower.tail=FALSE, df= 1) [1] 0.1929690 There wasn't difference between the models. Must i choose the most parsimonious model? Thanks for your attention and sorry for the inconvenience. -- View this message in context: http://r.789695.n4.nabble.com/Using-the-zero-inflated-binomial-in-experimental-designs-tp2221254p2223819.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.