similar to: Subpopulations in Complex Surveys

Hi, I have been experimenting with the new Survey package. Specifically, I was trying to use some of the functions on the public-use survey data from NHIS (2000 Sample Adult file). Error 1): The first error I get is when I try to specify the complex survey design. nhis.design<-svydesign(ids=~psu, probs=~probs, strata=~strata, data=nhis.df, check.strata=TRUE) Error in svydesign(ids =

Hi everyone, my apologies in advance if I'm overlooking something simple in this question. I am trying to use R's survey package to make a direct method age-adjustment to some complex survey data. I have played with postStratify, calibrate, rake, and simply multiplying the base weights by the correct proportions - nothing seems to hit the published numbers on the nose. I am trying to

Hello, Although my R code for the svymean () and svyquantile () functions works fine, I am stuck with the svyby () and make.formula () functions. I got the following error messages. - Error: object of type 'closure' is not subsettable # svyby () - Error in xx[[1]] : subscript out of bounds # make.formula () A reproducible example is appended below. I would appreciate if

Dear members of the R help list, I want to do a hierarchical glm with binomial family but am unsure about how to write the syntax which involves nesting. I want to test whether the risk of being attacked by Herbivores for Meadowsweet plants is significantly dependent on the Distance to heterospecific source plants. Dependent variable = Herbivory (yes/no) Explanatory continuous variable =

Hi R users, I am trying to use the aggregate function with a survey design object and survey functions, but get the following error. I think I am incorrectly using the syntax somehow, and it may not be possible to access variables directly by name in a survey-design object. Am I right? How do I fix this problem? I have used aggregate with "mean" and "weighted.mean", and

I'm trying to use the survey package to calculate a risk difference with confidence interval for binge drinking between sexes. Variables are X_RFBING2 (Yes, No) and SEX. Both are factors. I can get the group prevalences easily enough with result <- svyby(~X_RFBING2, ~SEX, la04.svy, svymean, na.rm = TRUE) and then extract components from the svyby object with SE() and coef() to do the

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.

Hello, I am working with version 2.7.2 on a PC and have 2.8.0 available, but have not upgraded completely yet. I have 6 species for which I've run 6 unique environmental management scenarios against for comparison purposes. Each scenario is run for 36 years (1965 - 2000). Some of the species have subpopulations and other do not. For those with subpopulations (A, B, C, D, E, and F) I have

Hi everyone, apologies if the answer to this is in an obvious place. I've been searching for about a day and haven't found anything.. I'm trying to replicate Stata's confidence intervals in R with the survey package, and the numbers are very very close but not exact. My ultimate goal is to replicate Berkeley's SDA website with R (http://sda.berkeley.edu/), which seems to

To whom it may concern, I have a question referring to the calculation of variance estimation of the survey package I need to estimate the variance for different Domains but for a stratified sampling desing in several stages. Särndal et al (1992), CAP 10, makes reference to this problem. My question is if it is possible by means of "survey package" to obtain these

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

Hello, I still apologise if the question i ask is naive. I would like to use R instead of usual softs (SAS, Stata) or at list to do things that the others do not. As a consequence I am trying to get familiar with R, and i am astonished because it does not seem to do things that are easy to do on other softs. I have got data with missing values (I am working on a questionnaire filled by students)

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,

Hi, i read something about MECOSA3 (G.Arminger) which is a software to : "Analysis of finite mixtures of conditional Lisrel models" I'm very interested to identify heterogeneous subpopulations and ask me are similar functions doing something in R, too ??? I know SEM and perhaps with some additions/modifications it is possible doing this general mean- and covariance structures with

Test =) soddsjbmshdwqwu -- Test, yep.

Hello, The following code is expected to produce 4 charts. But, I only get charts 1,2 ,& 4, NOT CHART # 3. For Chart# 3, I am getting the following error message: Error in tapply(1:NROW(x), list(factor(strata)), function(index) { : arguments must have same length I would appreciate if someone could help me resolve the issue. Thanks, Pradip # BELOW IS THE REPRODUCIBLE EXAMPLE setwd

Hello I'm trying to get the proportion "true" for dichotomous variable for various subgroups in a survey. This works fine, but obviously doesn't give proportions directly: svytable(~SurvYear+problem.vandal, seh.dsn, round=TRUE) problem.vandal SurvYear FALSE TRUE 1995 8906 786 1997 17164 2494 1998 17890 1921 1999 18322 1669 2001 17623 2122 ...

Dear Helpers   I have a sample frame and i have sampled from it using three methods and now i want to calculate the statistics but i only get the population parameters.   H <- matrix(rnorm(100, mean=50000, sd=5000)) sampleframe=data.frame(type=c(rep("H",100)),value=c(H)) sampleframe   str=strata(sampleframe,c("type"),size=c(20,), method="srswor")

I am trying to use tree to partition a data set. The data set has 3924 observations. Partitioning seems to work for small subsets of the data, but when I use the entire data set, no partitioning occurs. The variables are: RESP respondent to a survey (0 = not a respondent, 1 = respondent) AGE_P Age (continuous) ORIGIN_I Hispanic Ethnicity (1 = Hispanic, 2 = non-Hispanic) RACRECI2 Race

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