similar to: neg-bin clustered analysis in R?

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 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

Dear R-list, maybe someone can help me with the following mixed-effects models problem, as I am unable to figure it out with the 'nlme-bible'. I would like to fit (in R, obviously) a so-called animal model (google e. g. "Heritability and genetic constraints of life-history" by Pettay et al.) to estimate the variance component that is due to genetic effects. The covariances of

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).

Greetings glmmADMB function users, I am trying to run a series of models using the glmmADMB function with several different distribution families (e.g., poisson, negbinom). I am using a Optiplex 790 PC with Windows 7, 16.0 GB of RAM and a 64-bit operating system. I am running R version 2.15.0 and started out using the most recent version of glmmADMB (I believe version 7.2.15). My data is zero

Hi, I have to analyse the number of provisioning trips to nestlings according to a number of biological and environmental factors. I was thinking of building a mixed-effects model with species and nestid as random effects, using a Poisson distribution, but the data are overdispersed (variance/mean = 5). I then thought of using a mixed-effects model with negative binomial distribution, but I have

Hi there, I have relative abundance data for 13 mammal species that I collected at various sites that ranged in road density. I'm trying to determine the effect of road density on animal abundance across body sizes. For most species, I have data that was collected in one year but for a few species I have two years of complete data, and would like to use both. Since I have count data, I'm

Dear all, I was wondering whether anyone knows about a program which converts (part of) a data definition file (such as a .dct file for stata, or .sas file for sas) into an R-script. Here is an example with a .sas file: <-- snipp VALUE HTYPE (default=32) 0 = "Not in household" 1 = "Married couple family household" 2 =

Dear R users, I am trying to convert a dataset from one format to several rectangular datasets. A consultant helped design the data entry program for our survey using Delphi/Pascal and for each household the information is stored in a file called "EA-HM-HH.TXT" where EA is the enumeration area number, HM is the homestead number and HH is the household number. Within this file the

I have a people table with four types of people: clients, spouses, children, and others all setup using single-table inheritance with a foreign key back to a household record. A Household has_one client and spouse, and has_many children and others. I want to use a single "Household.find(@session [:household_id], :include => [:client, :spouse, :children, :others])"

Hi R-users!! I have some trouble with the survey pakage and i would be very glad if you can give me an advice. I have a sample from a survey where household were interviewed. The sample has 4 criteria on which the stratification was based: REGION, SIZE OF HOUSEHOLD, SIZE OF LOCALITY, AGE OF HEAD OF HOUSEHOLD. Since i don't have the whole information in each cell of the cross

Hello, I need some help in creating a new variable. I need to create a 'couple identifier', which gives a unique code for every couple/triple/... in a household. So, I can identify couples. To do this, I should use 4 variables: * SERIAL = a unique numeric code for each household * PERNUM = a unique numeric code for each person * SPLOC = the numeric code of the spouse in the

Dear all, sorry, this is for sure really basic, but I searched a lot in the internet, and just couldn't find a solution. The problem is to create new variables from a data frame which contains both individual and group variables, such as mean age for an household. My data frame: df hhid h.age 1 10010020 23 2 10010020 23 3 10010126 42 4 10010126 60 5 10010142

Dear R-users, Recently I had to analyze a dataset from household survey. The sample design ensured, that each household in the population has the same probability of being sampled. However the data were gathered from only one adult individual in each household, who was randomly choosen by an interviewer (via "Kish grid"). To equalize the probabilities for each INDIVIDUAL a casewise

Hi all, I have a dataset of individuals where the variable ID corresponds to the identification of the household where the individual lives. rel.head stands for the relationship with the household head. so rel.head=1 is the household head, rel.head=2 is the spouse, rel.head=3 is the children. Here is an example to see how it looks like: df<-data.frame(ID=c("17100",

Good afternoon! As mentioned in the subject, my question regards more the methodological part that accompanies survey design and the statistical part that is involved. So, I have the following data: a<-data.frame (id_hh=c(1:5), strata=c(1,1,2,2,1), Nhstrata=c(100,100,200,200,100), Nrmemb=c(2,4,2,5,4)) a$ocmemb1<-c("wk","jl","st","jl","st")

Hi, I am trying to run a logistic regression to look at the risk of malaria infection in individuals. I want to account for intra household correlation and so want to include a household level random effect. I have been using the lmer command in lme4 package but am getting some strange results that are completely different to those I get using STATA. Can I just check that this is the correct

I have the following sample dataset (CSV input here:http://goo.gl/YR8LP. CSV output here: http://goo.gl/EFCC8) which I want to transform as follows. For each person in a household I want to create two new variables OrigTAZ and DestTAZ. It should take the value in TripendTAZ and put that in DestTAZ. For OrigTAZ it should put value of TripendTAZ from the previous row. For the first trip of every

I would appreciate help in knowing how to repeat categorical variable code given in column=A, by the number in a matching column=B. For example, I have a categorical variable code attributed to a household=A and want to replicate the code for all member of the household, as given in column=B. I would like to have one sequence of categorical variable codes for individuals in column C. I have ~9000

I am attempting to build a package on r-forge and running into a weird error. I have been in correspondence with the R-forge admins and am turning to r-devel on the remote chance that someone might have a guess as to what is going wrong or a suggestion about further diagnostics/experiments I could try ... The package seems to build fine on my system(s) with R CMD build --compact-vignettes