-------- Original Message -------- Subject: RE: regression of Procrustes coordinates on classifiers Date: Fri, 27 Feb 2009 07:02:20 -0800 (PST) From: F. James Rohlf <[email protected]> Reply-To: [email protected] Organization: Stony Brook University To: [email protected] References: <[email protected]> Actually, you would use logistic regression if the _dependent_ (not independent) variable was binomially distributed rather than normally distributed. The assumption for the independent variables is that they are known without error (or at least relatively little error compared to the dependent variable). If this assumption is not met then the test is still valid but the regression coefficients will be biased downward. ------------------------ F. James Rohlf, Distinguished Professor Ecology & Evolution, Stony Brook University www: http://life.bio.sunysb.edu/ee/rohlf
-----Original Message----- From: morphmet [mailto:[email protected]] Sent: Friday, February 27, 2009 9:01 AM To: morphmet Subject: regression of Procrustes coordinates on classifiers -------- Original Message -------- Subject: regression of Procrustes coordinates on classifiers Date: Fri, 27 Feb 2009 05:55:11 -0800 (PST) From: Louis Boell <[email protected]> To: <[email protected]> Dear colleagues, I wish to investigate how strongly the fact that a sample of specimens belongs to a given class, say, samples from desert vs samples from forest, influences the Mahalanobis distances between my samples. This amounts to "correcting" for the desert vs forest "factor" and checking how much smaller the Mahalanobis distances between desert and forest samples get when calculated from the residuals of the "correction". I have about 10 samples per class (each sample in itself consisting of enough specimens given the number of landmarks) from each class). In this situation, I tried "correction" by using a dummy-coded regression (desert=1, forest=2) of Procrustes coordinates on my factor in MorphoJ. The results are appealing. Now I know that for a noncontinoous independent variable, you´d prefer to use logistic regression instead of simple regression, because the fit will be more appropriate in this case. My question is: is there a statistical reason not to use this procedure? Or caution about the interpretation of the results? I´d be grateful for any advice Best wishes Louis Louis Boell MPI für Evolutionsbiologie August-Thienemannstr.2 24306 Plön [email protected] [email protected] ----------------------------------------------------------------------- - Sicher, schnell, übersichtlich - der Internet Browser vom Marktführer! <http://redirect.gimas.net/?n=M0902IE8beta> -- Replies will be sent to the list. For more information visit http://www.morphometrics.org
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