similar to: Mixed-effects models / heterogeneous covariances

> Message: 24 > Date: Tue, 31 Jan 2006 18:22:52 +0000 > From: "Lutz Ph. Breitling" <lutz.breitling at gmail.com> > Subject: [R] Mixed-effects models / heterogeneous covariances > To: r-help at stat.math.ethz.ch > Message-ID: > <2e38a1c80601311022i2e1be92doa60b80b50b69eb0c at mail.gmail.com> > Content-Type: text/plain; charset=ISO-8859-1 > > Dear

Dear all, i am trying to redo the 'eyestudy' analysis presented on the site http://www.ats.ucla.edu/stat/stata/faq/relative_risk.htm with R (1.9.0), with special interest in the section on "relative risk estimation by poisson regression with robust error variance". so i guess rlm is the function to use. but what is its equivalent to the glm's argument "family"

Dear All, I'm analysing a negative binomial dataset from a population-based study. Many covariates were determined on household level, so all members of a household have the same value for those covariates. In STATA, there seems to be an option for 'clustered analysis' for neg-bin regression. Does an equivalent exist for R(MASS)'s glm.nb or a comparable function? Many thanks for

Dear List, having searched the help and archives, I have the impression that there is no automatic model selection procedure implemented in R that includes/excludes predictors in logistic regression models based on LRT P-values. Is that true, or is someone aware of an appropriate function somewhere in a custom package? Even if automatic model selection and LRT might not be the most appropriate

Hi R community, I am new bird to R and moved recently from SAS. I am no means expert on either but very curious learner. So your help crucial for me to learn R. I have already got positive expression. I was trying to fit a mixed model in animal experiment but stuck at simple point. The following similar example is from SAS mixed model pp 212. # data genetic_evaluation <-

Hello, I'm looking for a method to estimate narrow sense heritability of traits in a RIL population. Papers I've checked either use either SAS or SPSS or do not give any details at all. I've found some reference to using variance components in ANOVA, using the kinship or wgaim packages, but I don't have a clue as to how to do any of this. Is there any way fro a very R illiterate

Hello, I am trying to make the switch from SAS, and I have a fairly elemental problem with syntax using the nlme package for analyzing mixed models. There was a previous question on this topic posted to this list, so I apologize for redundancy, but I didn't understand the advice given to that inquiry. The model I want to run has the following factors: Host (fixed) Sire (random) Dam

Hi Everyone, I posted a similar question about a week ago, but haven't gotten any replies -- I'm afraid that's because my previous question was too vague. Let me try again with a more specific question, and I hope someone can help. NOTE, I know I should be using the newer lme4 package, I just haven't had a chance to update my version of R yet, so the question below relates

Hi R help, I wanted to set a fixed heritability for the object "Trait" left of ~ operator. Is this possible using lme, or would I need to use something like gls? This is the model line contained within a function; lme.out <- summary(lme(Trait ~ genotype, random = ~1|sire, weights=~number, na.action="na.omit")) Many thanks for any help.

Dear lists, I want to construct a loop in R, but don't know how to do it. I can do it in SAS, but I prefer in R (which I am hoping I will off SAS for good soon). Could anyone help me to convert the SAS codes to equivalent R codes. Basically, the following codes were written to establish the sire gametes or phases for daughter design for one markers two alleles. Here are the SAS code: do

Hi All, I'd like to ask for a few clarifications. I am doing some calculations over some biggish datasets. One has ~ 23000 rows, and 6 columns, the other has ~620000 rows and 6 columns. I am using these datasets to perform a simulation of of haplotype coalescence over a pedigree (the datestes themselves are pedigree information). I created a new dataset (same number of rows as the pedigree

Dear R helpers I have a table and i need to make new table table1: sire snp1 snp2 snp3 snp4 snp5 snp6 snp7 snp8 snp9 snp10 snp11 snp12 snp13 snp14 snp15 8877 -1 -1 -1 -1 0 0 -1 -1 -1 0 1 1 1 -1 -1 7765 1 1 1 0 0 0 -1 1 1 1 0 0 0 1 0 8766 1 1 -1 0 -1 -1 0 -1 0 -1 -1 -1 0 1 0 6756 0 1 0 -1 1 -1 -1 0 0 0 0 -1 0 1 1 5644 -1 0 1 -1 0 0 0 0 -1 -1 0 0 0 0 1 I have table2 sire

Hi to all, I was looking in google and also in this mailing list, but I dont find the solution to my problem, so I subscribe me to the list in order to post this e-mail and find the solution. This is the scenario: GSM Phone ----- GSM Network ---- TDM2406E --- ASterisk 1.4.0 (*) -------- VoIP Provider ------- Sip Phone or H323 Phone The problem is that I am generating calls from SIP and also

Hi, I have a dataframe that contains pedigree information; that is individual, sire and dam identities as separate columns. It also has date of birth. These identifiers are not numeric, or not sequential. Obviously, an identifier can appear in one or two columns, depending on whether it was a parent or not. These should be consistent. Not all identifiers appear in the individual column - it is

I have a data frame containing the Id, Mother, Father and Sex from about 10,000 animals in our colony. I am interested in graphing simple family trees for a given subject or small number of subjects. The basic idea is: start with data frame from entire colony and list of index animals. I need to identify all immediate relatives of these index animals and plot the pedigree for them. We're

Dear R People I figured it out. I should RTFM before asking questions, particularly on Saturday nights! Thanks for your patience. Sincerely, Erin -- Erin Hodgess Associate Professor Department of Computer and Mathematical Sciences University of Houston - Downtown mailto: erinm.hodgess at gmail.com

-------- Original Message -------- Subject: [AGDG-LIST:405] R Computing Contest Date: Sat, 21 Oct 2006 12:08:13 -0400 From: Larry Schaeffer <lrs at uoguelph.ca> Reply-To: lrs at uoguelph.ca To: Animal Geneticist's Discussion <agdg-list at colostate.edu> For those that are interested only: R Computer Programming Challenge Given: y = Factor A + Factor B + b1(Covariate1) +

Hi all, I'm having a problem with the auto.key function in xyplot. I changed the symbols an lines styles using these commands trellis.par.set(superpose.symbol=list(pch=c(0,1,2,3,4,5,6,8,15,16))) trellis.par.set(superpose.symbol=list(col=c(rep("black",11)))) trellis.par.set(superpose.symbol=list(cex=c(rep(0.6,11))))

Dear List, recently tried to reproduce the results of some custom model selection function after updating R, which unfortunately failed. However, I ultimately found the issue to be that testing with pchisq() in drop1() seems to have changed. In the below example, earlier versions (e.g. R 2.4.1) produce a missing P-value for the variable x, while newer versions (e.g. R 2.7.1) produce 0 (2.2e-16).

Hi, I'm running into a problem subsetting a data frame that I have never encountered before: > dim(chkPd) [1] 3213 6 > df = head(chkPd) > df PN WB Sire Dam MG SEX 601 1001 715349 61710 61702 67 F 969 1001_1 511092 616253 615037 168 F 986 1002_1 511082 616253 623905 168 F 667 1003 715617 61817 61441 67 F