Coefficient of determination (R^2) when using lme()
The question should be: "What is one trying to estimate?" Or "What is one trying to measure?" Until that is settled, no amount of research will go anywhere useful. Once it is settled, an answer may be quickly forthcoming. R^2 ought not to be treated as a quantity that has a magic that is independent of meaningfulness. Often, it has no meaningfulness that is relevant to the intended use of the regression results. If used at all adjusted R^2 is preferable to R^2. R^2 is a design measure, estimating how effectively the data are designed to extract a regression signal. Change the design (e.g., in a linear regression by doubling the range of values of the explanatory variable), and one changes (in this case, very substantially increases) the expected value of R^2. It can also be used as a rather crude way to compare two models for the one set of data, i.e., with the same 'design'. But be careful, replacing y by log(y) can increase R^2 and give a model that fits less well, or vice versa. Consider why that might be! What aspect of the 'design' that underpins your multilevel model do you wish to characterize? John Maindonald email: john.maindonald at anu.edu.au phone : +61 2 (6125)3473 fax : +61 2(6125)5549 Centre for Mathematics & Its Applications, Room 1194, John Dedman Mathematical Sciences Building (Building 27) Australian National University, Canberra ACT 0200.
On 1 Apr 2008, at 10:54 PM, vito muggeo wrote:
Dear R.S. Cotter, I think that interpretation of R2 is not straightforward and it is area of research.. Have a look to Xu. Measuring explained variation in linear mixed effects models Statist. Med. 2003; 22:3527?3541 (DOI: 10.1002/sim.1572) Orelien, J.G., Edwards, L.J., Fixed-effect variable selection in linear mixed models using R2 statistics Comput. Statist. Data Anal. (2007), doi: 10.1016/j.csda.2007.06.006 Hope this helps you, vito R.S. Cotter ha scritto:
Dear mixed models users, I have recently started using R, and I have learned to use lme (). Is it possible to interpret coefficient of determination (R^2) when using lme ()? Best Regards R.S. Cotter
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