similar to: how to extract p values in svyglm

Hello, I have a simple question: I want to list numbers 1:k, but if k <1, I hope nothing listed. how should we do? k=2 for (i in 1:k)  print(i) [1] 1    # <-correct [1] 2 k=0 for (i in 1:k) print(i) [1] 1      #<---- wrong [1] 0   thanks jian [[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

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.

Hi all, I have made an overdispersion test for a data set and get the following result Overdispersion test Obs.Var/Theor.Var Statistic p-value poisson data 16.24267 47444.85 0 after deleting the outliers from the data set I get the following result Overdispersion test Obs.Var/Theor.Var Statistic p-value poisson data 16.27106 0 1 The

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

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

Hello I want to know if the summary of the logistic model with survey Pr (> | t |) to test if the coefficient of the model is significant, ie is the p_valor wald test for the model coefficients, for I am interested to know if the three levels of the variable educational level are significant to the model (significance of handling 0.2), I present below the results of my model

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 a problem with the predict function of svyglm: When I try to predict with an object of svyglm I get the error message that R can't allocate a vector about 3 GB big. Has anybody a hint how I can reduce the memory used for this? I have about 25000 observation and use the weigths parameter. Where is so much data created? Thanks, Werner

Dear list, I am using svyglm in the survey library to fit a binomial logistic regression accounting for sample design. The documentation says the models are not fit by maximum likelihood, so my question is what is the fitting method? Pseudo likelihood? Generalized least squares? Thanks for any insight. Best, Corey Corey Sparks Assistant Professor Department of Demography and

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

Given: data(AirPassengers) I get a ts data structure AirPassengers in the workspace. How can I generate the code that can create that structure? That is, given an example of a data structure, is there a way to generate the code that can greate that structure? Alternatively, is there a reference that provides a list of dta structures together with a full list of theor respective attributes?

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 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

Greetings, I am revisiting code from several different files I have saved from the past and all used to run flawlessly; now when I run any of the svyglm related functions, I am coming up with an error: Error in model.frame.default(formula = F3ATTAINB ~ F1PARED, data = data, : the ... list does not contain 4 elements The following is a minimal reproducible example: library(RCurl)

Dear R helpers, For an allometric analysis (allometric equation y = a*x^b) I would like to apply a non-linear regression instead of using log-log transformations of the measured parameters x and y and a Model II linear regression. Since both of the variables x and y are random, I would like to apply a Model II non-linear analog of either Reduced Major Axis or Major Axis Regression. The

Sorry about re-posting this, it never went out to the mailing list when I posted this to r-help forum on Nabble and was pending for a few days, now that I am subscribe to the mailing list I hope that this goes out: I've been a viewer of this forum for a while and it has helped out a lot, but this is my first time posting something. I am running glm models for richness and abundances. For