search for: sasmac

...age where you can do ANOVA based trend analysis on grouped data > using orthogonal polynomial contrasts coefficients, for unequally > spaced factor levels. The closest hit I've had is from this web site: >(http://webcache.googleusercontent.com/search?q=cache:xN4K_KGuYGcJ:www.datavis.ca/sasmac/orpoly.html+Orthogonal+polynomial >l but I cannot find this package or anything like it. [[alternative HTML version deleted]]

Hello, for my meta-analysis I try to test if two varainces are equal without using the raw scores. I have is the SD's, N's and the Means. I want to test the variances from dependent and independend samples. I assume I can use the var.test procedure for the independent samples, but what about the dependent samples ? Has anyone an idea how to realise this with R ? Thanks in advance

Hi there, I'd like to plot some maps. Is it possible for me to use SAS map data in R? Thank you. Best, Junjie _________________________________________________________________ your life. [[alternative HTML version deleted]]

Hi, I have a two-way anova with unequal cell numbers that I want to analyze. The problem is I don't have individual observations of the data. I only have the sufficient statistics (mean, variance, # of observations) for each cell. Is there any existing function in S-plus that would allow me to do aov() with the sufficient statistics? The table is like G1 G2 G3 G5 G6 T1 T2 T3

Hello, I have a file with two dependent variables (three and five) and one independent variable. I do i.mod <- lm(cbind(three, five) ~ species, data=i.txt) and get the following output: Coefficients: three five (Intercept) 9.949 9.586 species -1.166 -1.156 I do a" i.can<-candisc(i.mod,data=i): and get the following output: Canonical Discriminant Analysis

Hi I am using the heatmap function in package mva to look at large correlation matrices visually. Is there any way to "flip" the output of heatmap plot left-right so that, if presented with a correlation matrix, it plots the unity elements in the correlation matrix along a diagonal from top left to bottom right? For example: library(mva) x = matrix(rnorm(1000), ncol=10) z = cor(x)

Dear all, I recently had to review the current litterature about some medical treatment with two possible variants (let's call them A and B). I collected all available prospective randomized trials about this treatment : I got four trials for the A variant and three for the B variant, all studies comparing one variant to a "suitably choosen" placebo. Two classes of variables are of