similar to: new version of survey package

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

Version 3.18 of the survey package is now percolating through CRAN. Since the last announcement on this list, in February, the main additions are - standard errors for survival curves (both Kaplan-Meier and Cox model) - svyciprop() for confidence intervals on proportions, especially in small samples or near 0 or 1. - predictive margins by direct standardization, with marginpred() -

Version 3.18 of the survey package is now percolating through CRAN. Since the last announcement on this list, in February, the main additions are - standard errors for survival curves (both Kaplan-Meier and Cox model) - svyciprop() for confidence intervals on proportions, especially in small samples or near 0 or 1. - predictive margins by direct standardization, with marginpred() -

Version 3.9 of the survey package is now on CRAN. Since the last announcement (version 3.6-11, about a year ago) the main changes are - Database-backed survey objects: the data can live in a SQLite (or other DBI-compatible) database and be loaded as needed. - Ordinal logistic regression - Support for the 'mitools' package and multiply-imputed data - Conditioning plots,

Version 3.9 of the survey package is now on CRAN. Since the last announcement (version 3.6-11, about a year ago) the main changes are - Database-backed survey objects: the data can live in a SQLite (or other DBI-compatible) database and be loaded as needed. - Ordinal logistic regression - Support for the 'mitools' package and multiply-imputed data - Conditioning plots,

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 =

Hello, all. I wanted to use the "survey" package to analyze data from the National Ambulatory Medical Care Survey, and am having some difficulty translating the analysis keywords from one package (Stata) to the other (R). The data were collected using a multistage probability sampling, and there are variables included to identify the sampling units and weights. Documentation from the

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

Version 3.11 of the survey package is making its way through CRAN. Since the last announcement on this list, of version 3.9, last September, there have been many minor bug fixes and usability improvements. The main new features are - loglinear models with svyloglin() - database-backed designs now allow new variables to be created, support ODBC in addition to DBI database interfaces, and

Version 3.11 of the survey package is making its way through CRAN. Since the last announcement on this list, of version 3.9, last September, there have been many minor bug fixes and usability improvements. The main new features are - loglinear models with svyloglin() - database-backed designs now allow new variables to be created, support ODBC in addition to DBI database interfaces, and

'surveyNG' version 0.3 is on CRAN. This package provides experimental features for survey analysis that may be incorporated in the survey package in the future. Currently there are facilities for analysis of complex surveys using (possibly large) data sets stored in a SQLite database. However, analysis facilities for these SQL-backed survey designs are rather more limited than in the

'surveyNG' version 0.3 is on CRAN. This package provides experimental features for survey analysis that may be incorporated in the survey package in the future. Currently there are facilities for analysis of complex surveys using (possibly large) data sets stored in a SQLite database. However, analysis facilities for these SQL-backed survey designs are rather more limited than in the

Hi, All Thanks to Robert Baskin, Thomas Lumley, and Spencer Graves for the valuable helps. I have learned a lot from this discussion. I put all discussions together without editing, so we can see how things are evolved. Likely, I have a lot of articles to read. As in the discussion, mixed modeling approach is a poosible but may be over-kill in my posted data analyses. I will explore other

Version 3.3 of "survey" is percolating through CRAN. Since the last announcement on this list, version 2.9, the main additions are calibration estimators: linear, bounded linear, raking ratio, bounded raking ratio, logit. Other updates and bug fixes are described in http://faculty.washington.edu/tlumley/survey/NEWS -thomas Thomas Lumley Assoc. Professor,

Version 3.3 of "survey" is percolating through CRAN. Since the last announcement on this list, version 2.9, the main additions are calibration estimators: linear, bounded linear, raking ratio, bounded raking ratio, logit. Other updates and bug fixes are described in http://faculty.washington.edu/tlumley/survey/NEWS -thomas Thomas Lumley Assoc. Professor,

-------------------------------------------------- From: "Ahoussou Sylvie" <sylvie.ahoussou at antilles.inra.fr> Sent: Friday, September 12, 2008 9:48 AM To: "Thomas Lumley" <tlumley at u.washington.edu> Subject: Re: [R] Complex sampling survey _ Use of survey package > Thanks for your answer > > I think I made a mistake when I recopied the 5 first rows of

Version 3.20 of the survey package is percolating through CRAN The major additions since the last announcement on this list (3.18, in September) are - database-backed designs can now use replicate weights - some multivariate statistics: principal components, factor analysis. The NEWS file has a more detailed list of additions and changes. -thomas Thomas Lumley Assoc.

Version 3.20 of the survey package is percolating through CRAN The major additions since the last announcement on this list (3.18, in September) are - database-backed designs can now use replicate weights - some multivariate statistics: principal components, factor analysis. The NEWS file has a more detailed list of additions and changes. -thomas Thomas Lumley Assoc.

Dear WizaRds, dear Thomas, First of all, I want to tell you how grateful I am for all your support. I wish I will be able to help others along one day the same way you do. Thank you so much. I am struggling with a multistage sampling design: library(survey) multi3 <- data.frame(cluster=c(1,1,1,1 ,2,2,2, 3,3), id=c(1,2,3,4, 1,2,3, 1,2), nl=c(4,4,4,4, 3,3,3, 2,2), Nl=c(100,100,100,100,

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?