hierarchical partitioning: type of R-squared
Good day Clement, and R users, I've used the hier.part package. I think that conceptually, if the form of relationship with the dependent variable differs among independent variables, hier.part won't provide unbiased results. Different samples from the same population should yield the same estimates of the relative contribution of different independent variables to (explained) variation in the dependent variable (Chevan and Sutherland 1991). If the form of the relationships between independent and the dependent variables differ, then you'd get different results from different samples, e.g. if one sample included more values of the dependent variable from one end of the possible range (?). Maybe someone can confirm or refute this? Or explain it better? Since I use this package, I'd like to clear up something I noticed in Clement's message: I thought that when using "R-squ" as the goodness of fit measures, unadjusted values were used. That seemed consistent with Pearson's correlation coefficients. Can anyone confirm? Thanks, Eric Howe -----Original Message----- From: r-sig-ecology-bounces at r-project.org [mailto:r-sig-ecology-bounces at r-project.org] On Behalf Of Cl?ment Tisseuil Sent: October 14, 2009 3:16 AM To: r-sig-ecology at r-project.org Subject: [R-sig-eco] hierarchical partitioning: adaptation and interpretation Dear R users, In the hier.part package, hierarchical partitioning is built upon a GLM (generalized linear model) framework to assess the independent and joint effect from a set of predictors onto a single quantitative response variable. In this context, the joint and independent effect from each factor can be evaluated throughout the R? calculation (adjusted). My two questions are: 1. Conceptually and from a statistical point of view, are there any problems to adapt the philosophy of hierarchical partitioning to a GAM (generalized additive model) framework when some quantitative predictors are supposed to have a non-linear effect with the response variable? 2. Let's say that the total variance of a single continuous variable can be explained by two qualitative factors (X1 and X2). I wonder if this total R? value resulting from the hier.part analysis (total=joint+independent value), and calculated individually for X1 and X2, can be discussed in terms of the inter-group variance (i.e. something like the variance between the means of each modalities of factors). If so, can the unexplained variation from the analysis (1- total R?) be associated to the intra-group variance (e.g. something like the variance within each modalities of factors)? . Thanks in advance for your help, Clement
Clement Tisseuil - PhD student Laboratoire "Evolution et Diversit? Biologique" (EDB) UMR 5174 - Universit? Paul Sabatier CNRS 118 route de Narbonne, B?t 4R3, Porte 112 31062 Toulouse Cedex 9 - France Phone : +33 5 61 55 67 35 Fax: +33 5 61 55 67 28 webpage: http://www.clement-tisseuil.eu [[alternative HTML version deleted]]