[R-sig-phylo] Can PGLS cope with collinearity between explanatory variables?
Hi all, I am testing a correlation between two explanatory variables and a response variable using PGLS. All of the variables are continuous. My model is Log female body size ~ Log egg size * Log clutch size. However, there is a significant negative correlation between egg size and clutch size. Can PGLS cope with collinearity between explanatory variables? Is there any way that I can apply something like principal component analysis to PGLS models? Thanks, Xu [[alternative HTML version deleted]] ___ R-sig-phylo mailing list R-sig-phylo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-phylo
Re: [R-sig-phylo] Can PGLS cope with collinearity between explanatory variables?
The issue of collinearity of independent variables is neither better nor worse with PGLS as opposed to OLS. Statistical significance per se of a correlation between X variables is not really the issue. How strong is the correlation? Most sources suggest that it needs to be greater than 0.7-0.8 in magnitude to cause serious problems. Cheers, Ted Theodore Garland, Jr. Professor Department of Biology University of California, Riverside Riverside, CA 92521 Office Phone: (951) 827-3524 Facsimile: (951) 827-4286 = Dept. office (not confidential) Email: tgarl...@ucr.edu http://www.biology.ucr.edu/people/faculty/Garland.html Experimental Evolution: Concepts, Methods, and Applications of Selection Experiments. 2009. Edited by Theodore Garland, Jr. and Michael R. Rose http://www.ucpress.edu/book.php?isbn=9780520261808 (PDFs of chapters are available from me or from the individual authors) From: r-sig-phylo-boun...@r-project.org [r-sig-phylo-boun...@r-project.org] on behalf of Xu Han [duck_han365...@hotmail.com] Sent: Friday, August 17, 2012 12:33 PM To: r-sig-phylo@r-project.org Subject: [R-sig-phylo] Can PGLS cope with collinearity between explanatory variables? Hi all, I am testing a correlation between two explanatory variables and a response variable using PGLS. All of the variables are continuous. My model is Log female body size ~ Log egg size * Log clutch size. However, there is a significant negative correlation between egg size and clutch size. Can PGLS cope with collinearity between explanatory variables? Is there any way that I can apply something like principal component analysis to PGLS models? Thanks, Xu [[alternative HTML version deleted]] ___ R-sig-phylo mailing list R-sig-phylo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-phylo ___ R-sig-phylo mailing list R-sig-phylo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-phylo
Re: [R-sig-phylo] Can PGLS cope with collinearity between explanatory variables?
Thanks Dr. Garland,The correlation between egg size and clutch size is 0.3, and the variance inflation factors for both egg size and clutch size are smaller than 2. There shouldn't be a big problem of collinearity. Thanks for your clarification.Best,Xu From: theodore.garl...@ucr.edu To: duck_han365...@hotmail.com; r-sig-phylo@r-project.org Subject: RE: [R-sig-phylo] Can PGLS cope with collinearity between explanatoryvariables? Date: Fri, 17 Aug 2012 19:38:31 + The issue of collinearity of independent variables is neither better nor worse with PGLS as opposed to OLS. Statistical significance per se of a correlation between X variables is not really the issue. How strong is the correlation? Most sources suggest that it needs to be greater than 0.7-0.8 in magnitude to cause serious problems. Cheers, Ted Theodore Garland, Jr. Professor Department of Biology University of California, Riverside Riverside, CA 92521 Office Phone: (951) 827-3524 Facsimile: (951) 827-4286 = Dept. office (not confidential) Email: tgarl...@ucr.edu http://www.biology.ucr.edu/people/faculty/Garland.html Experimental Evolution: Concepts, Methods, and Applications of Selection Experiments. 2009. Edited by Theodore Garland, Jr. and Michael R. Rose http://www.ucpress.edu/book.php?isbn=9780520261808 (PDFs of chapters are available from me or from the individual authors) From: r-sig-phylo-boun...@r-project.org [r-sig-phylo-boun...@r-project.org] on behalf of Xu Han [duck_han365...@hotmail.com] Sent: Friday, August 17, 2012 12:33 PM To: r-sig-phylo@r-project.org Subject: [R-sig-phylo] Can PGLS cope with collinearity between explanatory variables? Hi all, I am testing a correlation between two explanatory variables and a response variable using PGLS. All of the variables are continuous. My model is Log female body size ~ Log egg size * Log clutch size. However, there is a significant negative correlation between egg size and clutch size. Can PGLS cope with collinearity between explanatory variables? Is there any way that I can apply something like principal component analysis to PGLS models? Thanks, Xu [[alternative HTML version deleted]] ___ R-sig-phylo mailing list R-sig-phylo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-phylo [[alternative HTML version deleted]] ___ R-sig-phylo mailing list R-sig-phylo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-phylo
