Hello, Urs, you may have seen Wolfgang Viechtbauer's answer already which offers an R-technical solution, but this may leave the mathematical grounds of linear models. See inline below for my concern and a hint.
Am 17.05.2017 um 09:12 schrieb Urs Kleinholdermann:
Dear list members, I want to add a predictor to a linear model without changing the coefficients of the existing model. How is that done with R? So if I have a response y and predictors x1, x2, x3 I want to make a model lm1 like lm1 = lm(y~x1+x2) After this model is computed I want to add x3 like lm2 = lm(y~x1+x2+x3) However, unlike it is done by the notation above or by update or add1 (as far as I understand) I don't want a new model with all predictors estimated anew but I want a model lm2 where the coefficients for x1 and x2 stay exactly as in lm1 and the coefficent for x3 is estimated additionally. The reasons for this are theoretical.
And the reasons why this is usually impossible (for a valid linear model as a projection of the response vector onto a linear subspace spanned by the columns of the design matrix) are also theoretical: It is not an R problem, but a mathematical fact that unless the vector of values of a new model term is orthogonal to the vectors of all model terms already included in the model (i.e., to all columns of its design matrix) the estimated coefficients of the "old" model are correlated with the estimated coefficient of the "new" one, and hence the already existing ones change. So, if you manage to obtain orthogonality you can achieve what you desire. (You may want to consult with a (theoretical) book on linear models ... or a local statistician.) Hth -- Gerrit
I guess what I want is similar to calculating a new regression on the residuals of lm1. lm2 = lm(residuals(lm1)~x3) however, I would prefer to to that in the common framework of the lm command in order to calculate statistics, perform anova on the models and so on. thanks for your help! Urs ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.
______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.