salud=read.table("binarios.txt",header=TRUE) names(salud) salud$sexo=factor(salud$sexo) salud$educa=factor(salud$educa) salud$age=factor(salud$age) salud$bebedor=factor(salud$bebedor) salud$con_tab=factor(salud$con_tab) attach(salud) logistica1=glm(g02~sexo+bebedor,family=binomial(link=logit)) summary(logistica1) confint(logistica1) exp(coefficients(logistica1)) exp(confint(logistica1)) logistica2=glm(g02~sexo+p03,family=binomial(link=logit)) summary(logistica2) exp(coefficients(logistica2)) ajustados=logistica2$fitted ajustados=log(ajustados/(1-ajustados)) plot(p03,ajustados,type="n") points(p03[sexo==1],ajustados[sexo==1],col=2) points(p03[sexo==2],ajustados[sexo==2],col=4) logistica3=glm(g02~sexo*p03,family=binomial(link=logit)) summary(logistica3) exp(coefficients(logistica3)) ajustados2=logistica2$linear.predictor ajustados3=logistica3$linear.predictor par(mfrow=c(1,1)) plot(p03,ajustados2,type="n",main="sin interaccion") points(p03[sexo==1],ajustados2[sexo==1],col=2) points(p03[sexo==2],ajustados2[sexo==2],col=4) legend(130,1.5, col=c(2,4),pch=c(1,1),c("hombre","mujer")) plot(p03,ajustados3,type="n",main="con interaccion") points(p03[sexo==1],ajustados3[sexo==1],col=2) points(p03[sexo==2],ajustados3[sexo==2],col=4) legend(130,2, col=c(2,4),pch=c(1,1),c("hombre","mujer"))