similar to: svyglm fit method?

I am trying to read a SAS dataset into R that is in a .SD2 format, which is the Version 6 standard format from SAS. I see the routines that read the SAS XPORT format (foreign, Hmisc), but is there any way to read this one? Any help would be greatly appreciated. Corey Sparks Corey Sparks Assistant Professor Department of Demography and Organization Studies University of Texas-San Antonio One UTSA

Dear list, I am trying to use gregexpr to see if entries in a dataframe have either of two possible values for a string. here's an example text<-c("fat", "rat", "cat", "dog", "log", "fish") If I just wanted to find if any one of the elements in text match the pattern "at" I would do gregexpr("\\at", text)

Dear list, I have the function (as a simple example, which is actually part of a larger function) pres.test<-function(N0=N0, N1=N1) { dt<-5 r<-log(N1/N0)/dt r } which calculates the annual growth rates in a population Where N0 is the population classified into age intervals, say 5 years, at time=1995, and N1 is the population by 5 year age classes at time=2000.

Hello, I am running R 2.6.1 on windows xp I am trying to fit a cox proportional hazard model with a shared Gaussian frailty term using coxme My model is specified as: nofit1<-coxme(Surv(Age,cen1new)~ Sex+bo2+bo3,random=~1|isl,data=mydat) With x1-x3 being dummy variables, and isl being the community level variable with 4 levels. Does anyone know if there is a way to get the standard error

R won't appear under the applications. Go to the terminal (in the accessories menu) and type R. It will run in command line. You might also want to install r-base-dev if you want to compile libraries. Corey S. Sparks, Ph.D. Assistant Professor Department of Demography and Organization Studies University of Texas San Antonio One UTSA Circle San Antonio, TX 78249 email:corey.sparks at

Dear R Users, I'm working on a problem where I have a multivariate response vector of counts and a continuous predictor. I've thought about doing this the same way you would do a Multvariate regression model with normally distributed data, but since these data are counts, they are probably better modeled with a Poisson distribution. For example y1<-rpois(100,3.5) y2<-rpois(100,1.5)

Hi R users, I'm using the survey package to calculate summary statistics for a large health survey (the Demographic and Health Survey for Honduras, 2006), and when I try to calculate the variances for several variables, I get negative numbers. I thought it may be my data, so I ran the example on the help page: data(api) ## one-stage cluster sample dclus1<-svydesign(id=~dnum, weights=~pw,

Dear R users, I am interested in taking the columns from multiple dataframes, the problem is that the different dataframes have different combinations of the same variable names, here's a simple example: a<-rep(1:10) b<-rep(1:10) c<-rep(21:30) d<-rep(31:40) dat.a<-data.frame(a,b,c,d) names(dat.a)<-c("a", "b", "c", "d")

> Dear list, > > I have some data on a geneaology, here is a subset: > warmerge[1:11,c(1,6,25)] > Warrior SibID birth.year > 1100 3793 2013 1926 > 4 2013 2024 1934 > 1094 3769 2024 1918 > 632 2747 2037 1928 > 176 2083 2039 1944 > 187 2085 2039 1949 > 192 2086 2039 NA > 495

Hello list, I?ve been trying to get OpenBUGS running on my mac using the wine emulator. I can run Openbugs just fine by doing: wine ~/OpenBUGS312/OpenBUGS.exe In the terminal, so OpenBUGS works. When I try to run the schools example using rbugs(), the OpenBUGS process starts in wine, but it just sits there, no log, no script, no output of any sort. The rbugs () call makes the init,

Dear list, I am fitting a logistic multi-level regression model and need to test the difference between the ordinary logistic regression from a glm() fit and the mixed effects fit from glmer(), basically I want to do a likelihood ratio test between the two fits. The data are like this: My outcome is a (1,0) for health status, I have several (1,0) dummy variables RURAL, SMOKE, DRINK, EMPLOYED,

Hello, I'm trying to use the function svyglm in the library survey. I create a data survey object: data_svy<- svydesign(id=~PSU, strata=~sample_domain, weights=~sample_weight, data=data, nest=TRUE) and I try to use svyglm() with little success: R<-svyglm(data_svy[,4]~(data_svy[,iCol]==listModality[[iVar]] [iMod]),design=data_svy, family=binomial(link="logit") Error in

Hello! I am using for logistic regression in survey data the svyglm procedure. I wondered how does the strata effect estimates SE (in addition to the weights given proportional to population size). I know that for simple regression measurements of each strata is assumed to have different variance. But in a logistic model this is not the case. Can anyone help me here? Thank you Ron [[alternative

Hello, As obtained from a table svyglm clasificaion, sensitivity and specificity. The funtion ConfusionMatrix () of the library (caret) gives these results but not how to apply it to svyglm. thanks [[alternative HTML version deleted]]

Does anyone know how to calculated a BIC score (or an equivalent model fitness score) when using svyglm for logistic regressions? Thanks Brad -- View this message in context: http://r.789695.n4.nabble.com/Generating-a-model-fitness-when-score-using-svyglm-tp2069280p2069280.html Sent from the R help mailing list archive at Nabble.com.

Howdy, Referencing the below exchange: https://stat.ethz.ch/pipermail/r-help/2006-April/103862.html I am still getting the same warning ("non-integer #successes in a binomial glm!") when using svyglm:::survey. Using the API data: library(survey) data(api) #stratified sample dstrat<-svydesign(id=~1,strata=~stype, weights=~pw, data=apistrat, fpc=~fpc)

I?m running some logistic regressions and I?ve been trying to include weights in the equation. However, when I run the model, I get this warning message: Here?s what it says: Warning message: In eval(expr, envir, enclos) : non-integer #successes in a binomial glm! I think it is because the weights are non-integer values. What is a good way to run logistic regressions in R when using

Hi, I would like to estimate coefficients using poisson regression and then get standard errors that are adjusted for heteroskedasticity, using a complex sample survey data. Then I will calculate prevalence ratio and confidence intervals. Can sandwich estimator of variance be used when observations aren?t independent? In my case, observations are independent across groups (clusters), but

I have this problem. test <- svydesign(id=~1,weights=~peso) logit <- svyglm(bach ~ job2 + mujer + egp4 + programa + delay + mdeo + str + evprivate, family=binomial,design=test) then appear: Error in svyglm.survey.design(bach ~ job2 + mujer + egp4 + programa + : all variables must be in design= argument I don't know what this mean... Please help. Pablo. [[alternative HTML

Hello, I want to know how to perform stepwise elimination of variables to svyglm thanks [[alternative HTML version deleted]]