similar to: confidence intervals of proportions from complex surveys

Using the survey package I find it is convenient and easy to get estimated proportions using svymean, and their corresponding estimated standard errors. But is there any elegant/simple way to calculate corresponding confidence intervals for those proportions? Of course +/- 1.96 s.e. is a reasonable approximation for a 95% CI, but (incorrectly) assumes symmetrical distribution for a proportion.

Hi, is there a way to analyze subpopulations (e.g. women over 50, those who answered "yes" to a particular question) in a survey using Survey package? Other packages (e.g. Stata, SUDAAN) do this with a subpopulation option to identify the subpopulation for which the analysis shoud be done. I did not see this option in the Survey package. Is there another way to do this?

a closer look to the help on predict.glm will reveal that the function accepts a 'type' argument. In you case 'type = response' will give you the results in probabilities (that it seems to be what you are looking for). There also is an example on use of the 'type' argument at the end of the page. Stefano -----Messaggio originale----- Da: r-help-bounces at r-project.org

Hello R-list, I'm attempting to migrate from Stata to R for my complex survey work. It has been straight-forward so far except for the following problem: I have some code below, but first I'll describe the problem. When I compute predicted logits from a logistic regression, the standard errors of the predicted logits are way off (but the predicted logits are fine). Furthermore, the

Dear R users this may be a simple question - but i would appreciate any thoughts does anyone know how you would get one lower and one upper confidence interval for a set of data that consists of proportions. i.e. taking a usual confidence interval for normal data would result in the lower confidence interval being negative - which is not possible given the data (which is constrained between

Hello! I want to calculate simultaneous confidence intervals for a nominal variable with three categories: "yes", "no", "partially" and I expect that far more than 5 samples fall into each category. I have read that Glaz & Sison's method is only appropriate for variables with 7 or more categories. Therefore, the Goodman method seems like a good idea. I have

Dear all, Does someone know an R function implementing the method of Sison and Glaz (1995) (see full ref below) for computing Simultaneous confidence intervals for multinomial proportions? As alternative method, I think to boostrap the mean of each proportion and get in that way confidence interval of the mean. I observed 21 times a response that could be one out of 8 categories

Dear list colleagues, I'm trying to come up with a test question for undergraduates to illustrate comparison of means from a complex survey design. The data for the example looks roughly like this: mytest<-data.frame(harper=rnorm(500, mean=60, sd=1), party=sample(c("BQ", "NDP", "Conservative", "Liberal", "None", NA), size=500,

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

I have learned a lot from this list. I would like to thank the developers and contributors who devote so much of their time to this project. Does anyone know if any methods have been developed for handling data from complex sample surveys that include sample weights, clusters, strata, and so on? I know that SUDAAN, Stata have some abilities. Does anything exist in R/S? Paul E. Green

Hi Dear Rusers, I am working on a survey data with the "survey" package. The logistic regression and multinomial regression would be the main statistic method I want to use. I found that the svyglm function could be used to conduct the logistic regression with the complex design but not the multinomial regression. I wonder if there is any package or function in the "survey"

Can someone direct me to an R function that properly computes standard errors of data obtained from a complex survery design, i.e. perform alnalyses similiar to those that can be performed with SUDAAN, particularly for a non-parametric one-way ANOVA, e.g. signed rank test? Thanks, John John Sorkin M.D., Ph.D. Chief, Biostatistics and Informatics Baltimore VA Medical Center GRECC, University of

Greetings, I am using library(survey) to analyze some complex sample data. After fitting a model I tried to use termplot() with make.panel.svysmooth(), but I received an error (see below). Could someone help me interpret the error message so I can make the necessary corrections? The make.panel.svysmooth() function seems to work fine, and termplot() worked fine after I dropped the smoother.

I need some guidance from someone who is familiar/has some experience with the survey package. The data that I am using is from the Medical Expenditure Panel Survey (www.meps.ahrq.gov <http://www.meps.ahrq.gov/> ). The STRATA and PSU variables are varstr01 and varpsu01 respectively. When I try to specify them with the svydesign function I get an error message. An excerpt of my session

Hi, I would be very grateful for advice on getting confidence intervals for the ordinary (non smoothed) parameter estimates from a gam. Motivation I am studying hospital outcomes in a large data set. The outcomes of interest to me are all binary variables. The one in the example here, Dead30d, is death within 30 days of admission. Sexf is gender (M or F), Age is age in years at the start

Hello, is there anyone who has some ideas about the problem I posted? Help! [[alternative HTML version deleted]]

Dear R-list members, I´m using the package "survey" and I need to find a function for multinomial logistic regression in a complex design. The functions that I see are only for dicotomic and ordinal variables. Thank you! Rosario Austral ________________________________ De: "r-help-request@r-project.org" <r-help-request@r-project.org> Para:

Dear R-users, I want to multiple impute missing scores, but only for a few subgroups in my data (variable 'subgroups': only impute for subgroups 2 and 3). Does anyone knows how to do this in MICE? This is my script for the multiple imputation: imp <- mice(data, m=20, predictorMatrix=pred, post=post, method=c("", "", "", "",

Hi everyone, I'm having trouble figuring out how to split a dataframe more than once. Let's say I have a dataframe d with a certain column called splitcol composed of four possible ordinal values. The same dataframe has two other columns, col1 and col2, that have one of two possible values each. I'd like to split d$splitcol based on col1 and col2 so I can report frequencies of the

Hello, Does anyone know which method from Newcombe (1998)* is implemented in prop.test for comparing two proportions? I would guess it is the method based on the Wilson score (for single proportion), with and without continuity correction for prop.test(..., correct=FALSE) and prop.test(..., correct=TRUE). These methods would correspond to no. 10 and 11 tested in Newcombe, respectively. Can