similar to: Major Axis residuals

Also, this works (taking out multcomp=TRUE, multcompmethod="adjusted"): com.test=ma(Head.W1~Leg.3.1+Site, type="elevation", data=queens) print(com.test) ....so for some reason it will do an MA regression on all my data point together, but shows an error when I try to do pairwise comparisons between groups. Thank you, Ioulia -------- On Fri, May 11, 2012 at 2:09 AM, Ioulia

Hi there, I've been using the SMATR package to do standardized major axis (SMA) regression on allometric data, and I've been able to to pairwise comparisons of slope & elevation between multiple study sites. Now I'm trying to do the same thing using major axis (MA) regression, but I'm getting errors (SMATR should be able to do MA as well as SMA regression for everything,

Hi All, I am confused with SMATR's test for common slope. My null hypothesis here is that all slopes are parallel (common slopes?), right? So if I get a p value < 0.05 means that we can have confidence to reject it? That slopes are different? Or the other way around? it means that we have statistical confidence that the slopes are parallel? thanks -- Eugenio Larios PhD Student University

Hello all; My question is part statistical and part R. I have performed model II major axis regression in R using both the smatr() and lmodel2() packages, but neither offers an option to statistically weight my regression. I have a vector of weights which I would like to apply to each of my regression points (x vs. y), and was hoping that someone out there could provide me with some help on this

Hello, I am currently trying to run a series of models (all combinations of 4 independent factors, non-duplicate) and selecting the best one to describe my data. I was wondering if anyone knew of a way to get AIC and Likelihood values from R when using reduced major axis regression (RMA). I can get the values using the "lm" function, but that uses OLS to calculate the parameters. I

Hi, hres <- hclust(smatr,method="single") hresd<-as.dendrogram(hres) as.dendrogram(hres) `dendrogram' with 2 branches and 380 members total, at height 2514.513 plot(hresd,leaflab="none") #<-error here. #the plotted dendrogram is incomplete. The x axis is not drawn. #The interested reader can download the save(hresd,file="hres.rda") #from the

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Hi All Please see the Rprofile file which i have modified as follows and after that when I start R then I see that R says to me "TRUE" for all the packages implying that all loaded at once. But when i try to use commands as simple as help("lm"), it doesnt work nor any of the menu "Packages" is not working. Although the regression using lm ( Y ~ X ) is working

I have a glm regression (quasi-poisson) of log(mu) on x but I have varying degrees of confidence in the x values, and can attach a numerical weighting to each. Can anyone help me with suggestions of how to analysise this. Is there an R package that would help? Wendy [[alternative HTML version deleted]]

Hello, I am using function lmodel2 to calculate RMA regression between life-history traits in ladybirds beetles. It works well but I am not able to plot an RMA regression line on the scatterplot of my data. I am of course unable to plot the confidence intervals. For ordinary least square regression abline(lm(x~y))works well but for RMA regression, abline(lmodel2(x~y))does not do it. If somebody

[Originally sent this to r-help at lists.R-projects.org, but in case that's the wrong list I'm re-posting. Apologies if this becomes a re-post] -------------- next part -------------- An embedded message was scrubbed... From: Jonathon Kopecky <jkopecky at umich.edu> Subject: Need to fit a regression line using orthogonal residuals Date: Mon, 29 Jan 2007 14:52:24 -0500 Size: 1138

Hi, for testing if the slope of experimental data differs from a given slope I'm using the function "test_regression_against_slope" (see below). I am now confronted with the problem that I have data which requires a modelII regression (also called reduced major axes regression (RMA) or geometric mean regression). For this I use the function "modelII" (see below). What

Hello I'm using the package ade4 to obtain classification from a .txt file. I use the following commands: cronquist <- read.table("cronquist.txt", h = T, row.names = 8) cronquist <- as.taxo(cronquist[7:1]) cro.phy <- taxo2phylog(cronquist) in which cronquist.txt is a file with a classification of 218 genus of tree species from french Guiana. We I try to use the

CRAN (and crantastic) updates this week New packages ------------ * disclapmix (0.1) Maintainer: Mikkel Meyer Andersen Author(s): Mikkel Meyer Andersen and Poul Svante Eriksen License: GPL-2 http://crantastic.org/packages/disclapmix disclapmix makes inference in a mixture of Discrete Laplace distributions using the EM algorithm. * EstSimPDMP (1.1) Maintainer: Unknown Author(s):