Dear, I want to analyze an outcome in an RCT using lme but I am not sure that I have chosen the right way for the model. We measured the outcome three times repeatedly in the same patient. One time before intervention and two times after intervention. I wanted to adjust for the correlated data in the repeated measurement and baseline differences in the variable in order to get the treatment effect.
Here the model: lme(outcome~treatment*time+baseline; random=~1|id) for the data structure: id time outcome baseline treatment 1 1 10 5 1 1 2 12 5 1 2 1............ . . . alternatively I could use 3 rows per participant, omitting baseline as a variable as it would be included in "outcome" and "time" then. The model then would be: lme(outcome~treatment*time; random=~1|id) I am not sure which way is better/right or if there is a third alternative for this problem. Thanks in advance Steffen Fleischer ______________________________________________ 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.
