Thank you for your kindness, but ive done what you've said and the problem remains. What im doing is pretty straightforward,
>data response pred1 pred2 1 1 0 1 2 0 0 0 3 1 0 0 4 1 1 1 5 1 0 1 6 0 1 1 7 1 1 0 8 1 0 1 9 0 1 1 10 0 0 1 >sdata <- data[sample(nrow(data), 5), ] > sdata response pred1 pred2 8 1 0 1 2 0 0 0 9 0 1 1 10 0 0 1 6 0 1 1 >model<-glm(data$response~data$pred1+datos$pred2, family=binomial(link="logit")) > summary(model) ###the model ran correctly But when I ask for the predictions, > pred<- predict(model, newdata=sdata,type="response") Mensajes de aviso perdidos 'newdata' had 5 rows but variable(s) found have 10 rows > length(pred) [1] 10 And those 10 values are the fitted values corresponding for the model over its origin dataset. I really can't get what's the problem... -- View this message in context: http://r.789695.n4.nabble.com/Use-glm-coefficients-for-other-datasets-tp3276626p3296561.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.
