Hi, Not only odd, but impossible. If you have a model y ~ x1, and you *add* a new explanatory variable, you cannot get worse in raw R2. You can get worse in adjusted R2. You can also get worse if you add variables to a matrix for which you calculate distances. So dist(y) ~ dist([x1]) can have higher R2 than dist(y) ~ dist([x1,x2]) -- bioenv is based on this.
Cheers, Jari Oksanen Sent from my iPad > On 4.12.2013, at 20.19, "Sarah Goslee" <sarah.gos...@gmail.com> wrote: > > Hi, > > That seems a bit odd: can you provide a reproducible example, off-list > if necessary? > > Sarah > > > > On Wed, Dec 4, 2013 at 12:50 PM, Alexandre Fadigas de Souza > <alexso...@cb.ufrn.br> wrote: >> Dear friends, >> >> My name is Alexandre and I am trying to analyze a dataset on floristic >> composition of tropical coastal vegetation by means of variance partition, >> according to the outlines of a Tuomisto's recent papers, specially >> >> Tuomisto, H., Ruokolainen, L., Ruokolainen, K., 2012. Modelling niche and >> neutral dynamics : on the ecological interpretation of variation >> partitioning results. Ecography (Cop.). 35, 961–971. >> >> I have a doubt, could you please give your opinion on it? >> >> We are proceeding a variance partition of the bray-curtis floristic >> distance using as explanatory fractions soil nutrition, topography, canopy >> openess and geographical distances (all as euclidean distance matrices). >> >> We are using the MRM function of the ecodist package: >> >> mrm <- MRM(dist(species) ~ dist(soil) + dist(topograph) + dist(light) + >> dist(xy), data=my.data, nperm=10000 >> >> The idea is that the overall R2 of this multiple regression should be used >> to assess the contributions of the spatial and environmental fractions >> through subtraction : >> >> Three separate multiple regression analyses are needed >> to assess the relative explanatory power of geographical >> and environmental distances. All of these have the same >> response variable (the compositional dissimilarity matrix), >> but each analysis uses a diff erent set of the explanatory >> variables. In these analyses the explanatory variables are: >> (I) the geographical distance matrix only, (II) the environmental >> diff erence matrices only, and (III) all the explanatory >> variables used in (I) or (II). Comparing the R 2 values >> from these three analyses allows partitioning the variance >> of the response dissimilarity matrix to four fractions. >> Fraction A is explained uniquely by the environmental >> diff erence matrices and equals R2 (III) R2 (I). Fraction B >> is explained jointly by the environmental and geographical >> distances and equals R2 (I) R2 (II) R2 (III). Fraction C >> is explained uniquely by geographical distances and >> equals R2 (III) R2 (II). Fraction D is unexplained by the >> available environmental and geographical dissimilarity >> matrices and equals 100% R2 (III) (throughout the present >> paper, R2 values are expressed as percentages rather >> than proportions). [Tuomisto et al. 2012] >> >> The problem is that the R2 of the overall model (containing all the >> explanatory variables) is smaller than most of the R2 of models containing >> each of the explanatory matrices. So it seems not possible to proceed with >> the approach proposed. >> >> >> Sincerely, >> >> Alexandre >> >> Dr. Alexandre F. Souza >> Professor Adjunto II Departamento de Botanica, Ecologia e Zoologia >> Universidade Federal do Rio Grande do Norte (UFRN) >> http://www.docente.ufrn.br/alexsouza Curriculo: >> lattes.cnpq.br/7844758818522706 >> >> _______________________________________________ >> R-sig-ecology mailing list >> R-sig-ecology@r-project.org >> https://stat.ethz.ch/mailman/listinfo/r-sig-ecology > > > > -- > Sarah Goslee > http://www.stringpage.com > http://www.sarahgoslee.com > http://www.functionaldiversity.org > > _______________________________________________ > R-sig-ecology mailing list > R-sig-ecology@r-project.org > https://stat.ethz.ch/mailman/listinfo/r-sig-ecology _______________________________________________ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
