Hi all, I am kind of stuck of using Predict function in R to make prediction for a model with continuous variable and categorial variables. i have no problem making the model, the model is e.g.
cabbage.lm2<- lm(VitC ~ HeadWt + Date + Cult) HeadWt is a continuous variable, Date and Culte are factors. Date have three levels inside (d16,d20,d21), Cult has two levels(c39,c52). I need to calculate a confidence interval for the mean VitC for each combination of Date and Cult, fixing the value of HeadWt at the mean for the corresponding cell. I have already proved that Cult and Date are not interacted. the mean of HeadWt is also found. e.g.2.59 when i type > new.df<-data.frame(HeadWt=2.59,Cultc52=1,Dated16=1) > predict(cabbage.lm2,new.df, interval="confidence") it has error comes up like this: Error in model.frame.default(Terms, newdata, na.action = na.action, xlev = object$xlevels) : variable lengths differ (found for 'Cult') In addition: Warning message: 'newdata' had 1 rows but variable(s) found have 60 rows Is there anything I have done wrong?? Please help with the coding. Thank you so much!!! All the best. Andyer. ______________________________________________ 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.