similar to: svyglm.predict: cannot allocate vector

Hi, I have browsed the help list and looked at the FAQ but I don't find conclusive evidence if this is normal or I am doing something wrong. I am running a lm() on a data.frame with 27136 observations of 6 variables (3 num and 3 factor). After a while R throws this: > lm(log(y) ~ log(a) + log(b) + c + d + e, data=reg.data , na.action=na.exclude) Error: cannot allocate vector of size

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]]

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

Dear Professor Lumley I am relatively new to using R and also to logistic regression. We have analysed our Dudley Health Survey using the survey package. I am now trying to look at associations using svyglm but I am unsure of how to interpret the output and present the resulting model or whether there are any other things I should do to check the validity of the model. Below is an example of

Hi, this is probably the easiest thing to do but I manage not finding the answer: I have a list with matrices of exact same format and headers. Now I would like to transform the list into an normal array. What is the proper way to do this? as.array changes the entire format and right now I only found the method of creating a new array, going through the entire list and copy the matrix in each

Hi, probably just a quick question: can I somehow change the formula used with predict? E.g., the regression was run on "y ~ u + v + w" but for the prediction the term v should be removed from the formula contained in the regression object and only "y ~ u + w" be used. I could use model.matrix etc. to do the predictions but it would be very helpful to know a simpler way.

Hi, is anyone aware of estimation functions for threshold vector error correction / threshold cointegration models? I didn't find anything for R using RSeek or Google. Thanks a lot for any pointers, Werner __________________________________________________ Do You Yahoo!? hutz gegen Massenmails. http://mail.yahoo.com

Hi, is there a function in R to convert data read with read.shape and which is originally in UTM coordinates into longitude / latitude coordinates? I found the convUL() function from the PBSmapping package but I have no idea how I could apply that to the read.shape object. Many thanks, Werner __________________________________________________ Do sragenden Schutz gegen Massenmails.

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 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

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

Hi! I have large matrices, one column per variable and I have a vector of factors / grouping symbols. Then I am computing subtotals for the groups but it takes pretty long and thus I wanted to ask if there is a better way to do it or if this is already the best way: subTotals <- function(x, groupvec) do.call("rbind",lapply(split(x,groupvec),colSums,na.rm=T)) Thanks reading my

Hello, I'm running R 2.14.1 on OS X (x86_64-apple-darwin9.8.0/x86_64 (64-bit)), with version 3.28 of Thomas Lumley's survey package. I was using predict() from svyglm(). E.g.: data(api) dstrat<-svydesign(id=~1,strata=~stype, weights=~pw, data=apistrat, fpc=~fpc) out <- svyglm(sch.wide~ell+mobility, design=dstrat, family=quasibinomial()) pred.df <-

Hi, I was wondering if anybody might have a reference for me: My R code is growing and getting more and more confusing. Thus, I figure it's time to switch to object-oriented again. I have done oo programming in C++ and Java before but the first few tutorial on R oo were a bit confusing for me. Is there any brief tutorial on oo programming in R especially for people who have done oo in Java

Hi, I am trying to run analyzes incorporating sample weight, strata and cluster (three-stage sample) with PNS data (national health survey) and is giving error. I describe below the commands used. I could not make the code reproducible properly. Thanks, ################################################# library(survey)####change to 0 and 1 variable

Hi, I have two loosely related questions which could make my live again a bit easier: 1) Is there a simple way to select a range of columns in a data frame using column names? I am thinking of something like mydf[1,"col4":"col8"] 2) I have a data frame with many columns and they all have short variable names which is good in most cases but sometimes it would be nice to have

hi, i am not hitting an error when i copy and paste your code into a fresh console. maybe compare your sessionInfo() to mine? > sessionInfo() R version 3.4.1 (2017-06-30) Platform: x86_64-w64-mingw32/x64 (64-bit) Running under: Windows Server 2008 R2 x64 (build 7601) Service Pack 1 Matrix products: default locale: [1] LC_COLLATE=English_United States.1252

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