similar to: survey package svystat objects from predict()

Hi, I want to view the code for the function confint in the stats package. Typing just confint doesn't work. How can I view the code? Thanks, Walt ________________________ Walter R. Paczkowski, Ph.D. Data Analytics Corp. 44 Hamilton Lane Plainsboro, NJ 08536 ________________________ (V) 609-936-8999 (F) 609-936-3733 walt at dataanalyticscorp.com www.dataanalyticscorp.com

I have the following code which produces the output below it clus1 <- svydesign(ids = ~schid, data = lower_dat) items <- as.formula(paste(" ~ ", paste(lset, collapse= "+"))) rr1 <- svymean(items, clus1, deff='replace', na.rm=TRUE) > rr1 mean SE DEff W525209 0.719748 0.015606 2.4932 W525223 0.508228 0.027570 6.2802 W525035 0.827202

I have two indicator variables ABS and DEFF. I want to create another indicator variable which will take value 1 if either ABS=1 or DEFF=1. Otherwise, it will take value 0. How can I make that? [[alternative HTML version deleted]]

Hello, I have been using the Hmisc package's deff() command for some research with clustered data. I noticed that the formula to calculate the design effect seems a bit different. The formula for the DE is: 1 + rho*(B - 1) In most resources I have seen the formula for B to simply be the average number of observations in a cluster: n/k if n is the total sample size and k is the number of

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)

Dear List: I am working to understand some differences between the results of the svymean() function in the survey package and from code I have written myself. The results from svymean() also agree with results I get from SAS proc surveymeans, so, this suggests I am misunderstanding something. I am never comfortable with "I did what the software" does mentality, so I am working to

On Mon, Jun 21, 2010 at 9:37 AM, Aaron Gray <aaronngray.lists at gmail.com> wrote: > > Whats going on with having both write_uint32_le() > in WinCOFFObjectWriter::DefineSection() and WriteLE32() in > WinCOFFObjectWriter::WriteFileHeader() ? > Aaron Thanks, missed that one. Nathan used write_uint32_le in WinCOFF.h, and I guess accidentally used it in WinCOFFObjectWriter.cpp.

Just a quick question, My system is quite heavily customised with regard to permissions and MAC labels on system binaries. Is there any way to stop make installworld resetting all my customisation? At the moment I have a set of scripts to set permissions on everything but that's not exactly ideal. Mark -- PGP: http://www.darklogik.org/pub/pgp/pgp.txt B776 43DC 8A5D EAF9 2126 9A67 A7DA 390F

Dynamic DNS updating is failing (which is bizarre, because I could have sworn I'd had it working before). Help? Setup: Samba 4 DC running bind 9.9.2, Samba 3.6.3 member The output of "net -d10 ads join" is attached, compressed. Interesting portions of named.conf: options { (no allow-updates section) ... tkey-gssapi-keytab "/var/lib/samba/private/dns.keytab";

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

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

I have survey data that I am working on. I need to make some multi-way tables and regression analyses on the data. After attaching the data, this is the code I use for tables for four variables (sweight is the weight variable): > a <- xtabs(sweight~research.area + gender + a2n2 + age) > tmp <- ftable(a) Is this correct? I don't think I need to use the strata and cluster

Hi, I'm trying to setup IMC (idealx management console) to give our windows admins some nice toy to play with, but I have problem to make it work. I can log in after I authentificate as Administrator, but, I can't modify any LDAP entries, as that fails with unsufficient privileges due to the IMC trying to bind to LDAP as logged in user (Administrator), instead of something like

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

R-help, Sorry for this question (I guess it has been addressed before but I could not find it in the archives) but how can I see a function code when the following comes up: > svymean function (x, design, na.rm = FALSE, ...) { .svycheck(design) UseMethod("svymean", design) } <environment: namespace:survey> Thanks in advance

I am working on a new package, one in which the user needs to specify the role that different variables play in the analysis. Where I'm stumped is the best way to have users specify those roles. Approach #1: Separate formula for each special component First I thought to have users specify each formula separately, like: new.function(formula=y~X1+X2+X3, weights=~w,

I have updated my patch based on Chris'es feedback. I removed the dbgout_calls macro, but left others in place for now. If there are no objections, I would like to commit this tomorrow evening (~7PM GMT-7). I have compiled and tested it on MSVC, with Michaels testing code and it looks good. Once this is committed, Michaels patch can be applied. -Nathan -------------- next part --------------

Is there a way to use one of the functions in the survey package to get a table of estimated percentages (or proportions) and the standard error for each? For example, suppose that AGECODE AND SEX are two factors with 5 and 2 levels. The 5x2 AGECODE x SEX table would have the estimated percentage of persons in each cell, 100*(sum of weights in the cell) / (sum of all weights) and the std

Dear R users, I?m student of Master in Statistic and Data analysis, in New University of Lisbon. And now i?m writting my dissertation in variance estimation.So i?m using Survey Package to compute the principal estimators and theirs variances. My data is from Incoming and Expendire Survey. This is stratified Multi-stage Survey care out by National Statistic Institute of Mozambique. My domain of

On Thu, Mar 22, 2018 at 4:52 AM, Raja, Dr. Edwin Amalraj <amalraj.raja at abdn.ac.uk> wrote: > Hi , > > library(foreign) > write.dta(data1, "data1.dta") > > should work. I don't think so: > library(foreign) > example(svydesign) > write.dta(dstrat, "~/Downloads/foo.dta") Error in write.dta(dstrat, "~/Downloads/foo.dta") : The