similar to: Mixed-effects models: question about the syntax to introduce interactions

dfhfsdhf at ghghgr.com I ran a simple lme model: modelrandom=lmer(y~ (1|Test) + (1|strain), data=tempsub) Extracted the BLUPs: blups=ranef(modelrandom)[1] Even wrote myself a nice .csv file....: write.csv(ranef(modelrandom)[1],paste(x,"BLUPs.CSV")) This all works great. I end up with a .csv file with the names of my strains in the first column and the BLUP in the second

I've scoured the archives but have found no concrete answer to my question. Problem: Two data sets 1st data set(x) = 20,000 rows 2nd data set(y) = 5,000 rows Both have the same column names, the column of interest to me is a variable called strain. For example, a strain named "Chab1405" appears in x 150 times and in y 25 times... strain "Chab1999" only appears 200

Hi I am trying to install "lme4" package, but have problems intalling matrix package. I get the following error: RGui: Rgui.exe -Unable To Locate DLL the dynamic link library Rblas could not found in the specified path C:\Program

Dear R user, I have a question on using R to analyze data with repeated measurements. I have 2 species with several strains (12) per species, each of which has been measured twice with for a given trait. No particular covariance, just two measures. Now I want to analyze the data with an ANOVA (aov) considering these repeated measures to get the MSq and SSq for the species and strain level. I

I need to compare gene expression differences between multiple line pairs of alcohol preferring and non-preferring rat lines. I have 5 such line pairs, 3 are unrelated but two were derived independently from the same parent stock. For each line, there are 10 samples. I'll be testing multiple genes, but for simplicity assume just one gene whose expression is measures as geneExpression. Alcohol

Dear R users, Here is the coxme output I obtain on my survival dataset having 3 strains and 2 infection status (i: infected, ni: non infected) coxme(Surv(lay) ~ infection*strain, data=datalay, random= ~1 |block) Cox mixed-effects model fit by maximum likelihood Data: datalay n= 1194 Iterations= 3 77 NULL Integrated Penalized Log-likelihood -7270.028 -7223.859 -7218.175

Dear List, I downloaded R for the first time yesterday, in the hopes that I might deal more effectively with a complex repeated measures experimental design involving inbred strains of laboratory mice. The design below, somewhat simplified, cannot be computed with standard ANOVA, because something called the X'X matrix is too large. The design has the following factors: Between-subject

Dear list, Has anyone created a version of SSmicmen that allows testing for group differences? The basic Michaelis-Menten equation is: (Bmax * X) / (Kd + X). The nlme package allows modeling of random effects for Bmax and Kd as needed, but I curious how I can build in group differences? I have receptor binding data for strains of mice, and following Pinheiro and Bates' lead in their

Good morning, I'm trying to write a function to assign the mean separation grouping letters to the factors of an experiment. A client wants this so I thought I'd write my own function for future use. But I'm having trouble doing it because I don't understand the logic of the assignment. As a general example, consider the following data and the results from SAS and its weak

Hi, I am performing a repeated measures 2-way ANOVA to assess the influence of plant and leaf on aphid fecundity. Fecundity is measured for each aphid on a single leaf. Here is what I typed. wingless <- reshape(Wingless, varying =

I have assayed the concentrations of various metal elements in different anatomic regions of two strains of mice. Now, for each element, in each region, I want to do a t test to find whether there is any difference between the two strains. Here is what I did (using simulated data as an example): # create the data frame > elemconc = data.frame(expand.grid(id=1:3, geno=c('exp',

Dear all, I have some questions regarding the validity an implementation of statistical tests based on linear models and loess. I've searched the R-help arhives and found several informative threads that related to my questions, but there are still a few issues I'm not clear about. I'd be grateful for guidance. Background and data set: I wish to compare the growth and metabolism

Hi, I've got an array, say with i,jth entry = A_ij, and a vector, say with jth entry= v_j. I would like to multiply each column of the array by the corresponding vector component, i,e. find the array with i,jth entry A_ij * v_j This seems so basic but I can't figure out how to do it without a loop. Any suggestions? Michal.

We need to keep the discussion on the list. When I run your code, there are several problems. strain.data <- read.xlsx("Dee rhiz.xlsx", sheetName ="strain", header = T, row.names = 1) str(strain.data) # lists 9 columns at the end with all NAs strain.data1 <- (strain.data, sqrt.dist = TRUE) # this is not a valid R line. I get Error: unexpected ',' in

Hi, I am trying to parameterize the following mixed model (following Piepho and Ogutu 2002), to test for a trend over time, using multiple sites: y[ij]=mu+b[j]+a[i]+w[j]*(beta +t[i])+c[ij] where: y[ij]= a response variable at site i and year j mu = fixed intercept Beta=fixed slope w[j]=constant representing the jth year (covariate) b[j]=random effect of jth year, iid N(0,sigma2[b]) a[i]=random

Dear List I am having a bit of a problem getting a program to work. For each of i=1 to n persons I have a matrix (different for each person) with m rows. What I want to do, is create m new data sets such that the first is made up of the first row for each person from the original matrices, the second contains the second row for each person from the original matrices etc etc up to the mth

Hi I am using R to fit a survival function to my data (with a weibull distribution). Data: Survival of individuals in relation to 4 treatments ('a','b','c','g') syntax: ---- > survreg(Surv(date2)~males2, dist='weibull') But I have some problems interpreting the outcome and getting the parameters for each curve. --------- Value Std.

In the vcdExtra package on R-Forge, I have functions and generic methods for calculating log odds ratios for R x C x strata tables. I'd like to define methods for fitting weighted lm()s to the resulting loddsratio objects, but I'm having problems figuring out how to do this generally. # install.packages("vcdExtra", repos="http://R-Forge.R-Project.org")

Hello Sir I am getting problem in plotting in CCA . Could you please help me? I wrote the below command but I don't know why it is taking only first 5 env data rather than all 9. > strain.data <- read.xlsx("Dee rhiz.xlsx", sheetName="strain", header = T, row.names = 1) > env.data <- read.xlsx("Dee rhiz.xlsx", sheetName="env", header = T,

I would to know if it's possible with R put an apex on a character ( i.e 10-2 or aij ) Thanks in advance Damiano -------------- next part -------------- An HTML attachment was scrubbed... URL: https://stat.ethz.ch/pipermail/r-help/attachments/20011105/75518704/attachment.html