similar to: GLM different results with the same factors

Hi, I'm trying to make a model in order to know wich factors got?s influence in the intensity of a infection, but just in the individuals who's got this infection. In my data I've got a variable called "prevalence" with 2 levels: 1.- Infected individual 0.- Non infected So what i'm trying to do is a subset in a model like this,

I've run an ancova, edadysexo is a factor with 3 levels,and log(lcc) is the covariate (continous variable) I get this results > ancova<-aov(log(peso)~edadysexo*log(lcc)) > summary(ancova) Df Sum Sq Mean Sq F value Pr(>F) edadysexo 2 31.859 15.9294 803.9843 <2e-16 *** log(lcc) 1 11.389 11.3887 574.8081 <2e-16 ***

Hi, I'm working with R in windows and I wonder if there is any command (of the kind CTRL+ ) to transfer the commands I've worked with (like: > model<-glm(prevalencia~edadysexo*mes*zona,binomial)) to a script automatically, without the results I received from R after execute them. Another question, what's the combination of CTRL+ for transfer the orders in the other way, fom the

I've made fligner test with the same data, changing the orders of the variables, and this what i get > fligner.test(rojos~edadysexo*zona*ano*estacion) Fligner-Killeen test of homogeneity of variances data: rojos by edadysexo by zona by ano by estacion Fligner-Killeen:med chi-squared = 15.7651, df = 2, p-value = 0.0003773 > fligner.test(rojos~ano*edadysexo*zona*estacion)

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

Hi, I've got this model and following Hothorn et al advices, I used glht for a post hoc comparison > modezqM<-glm(rojos~estacion*zona3,quasipoisson,subset=(edadysexo=="M")) > anova(modezqM,test="F") Df Deviance Resid. Df Resid. Dev F Pr(>F) NULL 293 41148

Hi, I?ve got this model > model<-glm(prevalence~agesex+agesex:month,binomial) and the output of anova is like that > anova(model,test="Chisq") Df Deviance Resid. Df Resid. Dev P(>|Chi|) NULL 524 206.97 agesex 2 9.9165 522 197.05 0.007025 ** agesex:month 9 18.0899

Hello, I?m starting with my PhD and I have to stop because i got a little knowledge in R and statistics. I?ve got a model of this kind: binary response variable: prevalence of infection (0/1) 3 categorical independent variables: sex, month and name of the area I was trying with a full model like this, before the simplification model<-aov(prevalencia~sex*month*area) but the Fligner test

Se quiere hacer una encuesta de actitudes a una población de 45000 personas, quisiera me sugirieran un script adecuado , he revisado algunos en epicalc, pero no encuentro la respuesta adecuada (prevalencia 0,5, error 5%) -- Este mensaje le ha llegado mediante el servicio de correo electronico que ofrece Infomed para respaldar el cumplimiento de las misiones del Sistema Nacional de Salud.

Estimados amigos, Tengo el siguiente set de datos: caps <- datos[datos$NombreDepartamento=="LANUS", c("CAPS", "personas", "PersonasRCVG", "Con12Meses")] caps$prevalencia <- round(caps$PersonasRCVG/caps$personas*100,1) caps CAPS personas PersonasRCVG Con12Meses prevalencia 2345 2345 1347 132 211 9.8 2363