similar to: sensitivity and specificity in svyglm??

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

Hello, Seeking a way to get the variance inflation factor VIF for a model of regression in complex survey, I have understood that without this package (SURVEY) RGui VIF obtained as follows: fit <- lm(mpg~disp+hp+wt+drat, data=mtcars) vif(fit) But I want to know if survey, Vif is obtained so vif( svyglm(api00~ell+meals+mobility, design=dstrat)) Thank you, happy day

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

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

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

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)

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

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

summary(result) Call: svyglm(Injury ~ seat, sD, family = quasibinomial(link = "logit")) Survey design: svydesign(~1, prob = NULL, strata = Data[, 1], weights = Data[, 4], data = Data, fpc = ~fPc) Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -4.256875 0.001421 -2996.7 <2e-16 *** seatbad 0.681504 0.001689 403.4 <2e-16 *** ---

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

Hi all, I want to know how to perform the test Breslow-Day test for homogeneity of odds ratios (OR) stratified for svytable. This test is obtained with the following code: epi.2by2 (dat = daty, method = "case.control" conf.level = 0.95, units = 100, homogeneity = "breslow.day", verbose = TRUE) where "daty" is the object type table svytable consider it, but

Hello forum, I want to find in survey how to test V-cramer and coefficient Goodman-Kruskal gamma, to test the collinearity between varibles to enter a model. For the V-Cramer function is used with the package vcd assocstats but without considering the survey package. I appreciate the cooperation. Att. Diana Martinez [[alternative HTML version deleted]]

Hello forum, I want to do a test of independence with svychisq, but I get an error, then this my code: am18 <- read.spss("C:/Users/diana/Dropbox/Semestre 10/Tesis 10/Tesis Diana/AMcomuna18-29MAR2012.sav", use.value.labels=TRUE, max.value.labels=Inf, to.data.frame=TRUE) b<-matrix(c(am18$N6_MANZANA),ncol=1) c<-matrix(c(am18$PM1_1_PONDEMUESTRA),ncol=1)

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

Hi there I'm trying to fit a logistic regression model to data that looks very similar to the data in the sample below. I don't understand why I'm getting this error; none of the data are proportional and the weights are numeric values. Should I be concerned about the warning about non-integer successes in my binomial glm? If I should be, how do I go about addressing it? I'm