Dear list, I fitted a linear mixed effects model using lme in R on a relatively large data set. Now I want to extend this model, introducing an additional fixed effect on a subset of the data without altering coefficients estimated on the original dataset. I.e. original model for example: m1 = lme(y~a+b,random=~1|id,data=D) now I want to do something similiar to m2 = update(m1,~.+c,data=d) Where d is a subset of D. The values of the new predictor c are only available for this subset. However, I would like to keep the originally estimated coefficients of the model m1 with regard to predictors a and b. If I use update as described above coefficients for all predictors (a,b,c) are estimated again on the smaller dataset d. Any suggestions on how I can estimate the effect of c while keeping the old coefficient values for a and b? Or is this for some reason a bad idea altogether? Urs
How to extend an existing linear mixed effects model using lme in R?
2 messages · urs, Thierry Onkelinx
Dear Urs, What you can do is first get the predictions from m1 for dataset d and add it as a variable to dataset d. Then fit a model on dataset d using the prediction from m1 as an offset. d$M1 <- predict(m1, newdata = d, level = 0) m2 <- lme(y ~ offset(M1) + c, random = ~1|id, data = d) or d$M1 <- predict(m1, newdata = d, level = 1) m2 <- lm(y ~ offset(M1) + c, data = d) fitting m2 <- lme(y ~ a + b + c, random = ~1|id, data = d) will probably give a better fit. Best regards, Thierry ir. Thierry Onkelinx Instituut voor natuur- en bosonderzoek / Research Institute for Nature and Forest team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance Kliniekstraat 25 1070 Anderlecht Belgium To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to say what the experiment died of. ~ Sir Ronald Aylmer Fisher The plural of anecdote is not data. ~ Roger Brinner The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data. ~ John Tukey 2016-03-30 2:32 GMT+02:00 urs <urs at kleinholdermann.de>:
Dear list, I fitted a linear mixed effects model using lme in R on a relatively large data set. Now I want to extend this model, introducing an additional fixed effect on a subset of the data without altering coefficients estimated on the original dataset. I.e. original model for example: m1 = lme(y~a+b,random=~1|id,data=D) now I want to do something similiar to m2 = update(m1,~.+c,data=d) Where d is a subset of D. The values of the new predictor c are only available for this subset. However, I would like to keep the originally estimated coefficients of the model m1 with regard to predictors a and b. If I use update as described above coefficients for all predictors (a,b,c) are estimated again on the smaller dataset d. Any suggestions on how I can estimate the effect of c while keeping the old coefficient values for a and b? Or is this for some reason a bad idea altogether? Urs
_______________________________________________ R-sig-mixed-models at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models