similar to: wine survey: http://svy.mk/g7RhjY

Please take 10 minutes to complete this survey. Your answers will be completely anonymous. If you would like to be entered into a prize draw for a $50 Amazon gift card, please provide your email (optional). Winner will be notified on Friday, February 11. Your feedback will inform a Columbia University graduate student's thesis on boxed wine. http://www.surveymonkey.com/s/boxedwine

Dear list, I am trying to set up a propensity-weighted regression using the survey package. Most of my population is sampled with a sampling probability of one (that is, I have the full population). However, for a subset of the data I have only a 50% sample of the full population. In previous work on the data, I analyzed these data using SAS and STATA. In those packages I used a propensity weight

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'm studying the calibration function in the survey package in preparation for raking some survey data. Results from the rake function below agree with other sources. When I run calibrate, I get a warning message and the M and F weights seem to be reversed. Even allowing for that, the deviation between calibrated and raked weights is much more than I expected. I see that in the calibrate

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 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

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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

Hello, excuse me if this is trivial. I have some survey data with the following design MyDesign<-(id=ident, weights=~fwgt, fcp=~nval1+nval2, data=hh_data1) I would like to run simple frequency tables such as those provided by the freq() function of rgrs to check the impact of the sampling design on my Ns. Anyway I can do this? thanks, V [[alternative HTML version deleted]]

Dear all, I am looking for an equivalent of the pairwise.t.test() function using a complex survey design. Any suggestions on this or how to account for weights using the pairwise.t.test itself? Thanks, V [[alternative HTML version deleted]]

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]]

Hi R-help, I posted about this late yesterday but got no response. I may have put TMI in the original request. Not to mention I couldn't cut and paste yesterday because I was working R off a non-network computer while asking for help on a network computer. Essentially, I have this user-defined function: test <- function(X){ chisq <- svychisq(~X

John M. Chambers Statistical Software Award - 2008 Statistical Computing Section American Statistical Association The Statistical Computing Section of the American Statistical Association announces the competition for the John M. Chambers Statistical Software Award. In 1998 the Association for Computing Machinery presented its Software System Award to John Chambers for the design and

(sorry for cross-posting) John M. Chambers Statistical Software Award Statistical Computing Section American Statistical Association The Statistical Computing Section of the American Statistical Association announces the competition for the John M. Chambers Statistical Software Award. In 1998 the Association for Computing Machinery presented its Software System Award to John Chambers for the

John M. Chambers Statistical Software Award - 2009 Statistical Computing Section American Statistical Association The Statistical Computing Section of the American Statistical Association announces the competition for the John M. Chambers Statistical Software Award. In 1998 the Association for Computing Machinery presented its Software System Award to John Chambers for the design and development

{This was posted to S-news, but not on R-help, yet. It belongs here too. I've set "Reply-To" L.Galway, as for the S-news one. Thank you very much, John Chambers! Martin Maechler, R-help list moderator } John M. Chambers Statistical Software Award Statistical Computing Section American Statistical Association The Statistical Computing Section of the American Statistical

John M. Chambers Statistical Software Award - 2010 Statistical Computing Section American Statistical Association The Statistical Computing Section of the American Statistical Association announces the competition for the John M. Chambers Statistical Software Award. In 1998 the Association for Computing Machinery presented its Software System Award to John Chambers for the design and development

John M. Chambers Statistical Software Award - 2011 Statistical Computing Section American Statistical Association The Statistical Computing Section of the American Statistical Association announces the competition for the John M. Chambers Statistical Software Award. In 1998 the Association for Computing Machinery presented its Software System Award to John Chambers for the design and development

I am trying to use the reshape package for the first time. I have two waves of a survey, so the id variables include a subject identification number and a variable denoting the wave of the survey. I used the following arguments: library(reshape) svy.melt <- melt(svy, id=c("id", "WAVE")) svy.wide <- cast(svy.melt, id ~ WAVE + ...) and got the following error:

Hi all, I am running a set of logistic regressions, where we want to use some weights, and I am not sure whether what I am doing is reasonable or not. The dependent variable is turnout in an election - i.e. survey respondents were asked whether or not they voted. The percentage of those who say they voted is much higher than the actual turnout, probably due both to non-response bias and social