similar to: survey statistics, rate/proportions with standard errors

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

Hello: I am working with a stratified survey dataset with sampling weights and I want to use multiple imputation to help with missingness. 1. Is there a way to run an ordered logistic regression using both a multiply imputed dataset (i.e. from mice) and adjust for the survey characteristics using the weight variable? The Zelig package is able to do binary logistic regressions for survey

Dear there, I am working on the NHANES survey data, and want to apply quantile regression on these complex survey data. Does anyone know how to do this? Thank you in advance, Yiling Cheng Yiling J. Cheng MD, PhD Epidemiologist CoCHP, Division of Diabetes Translation Centers for Disease Control and Prevention 4770 Buford Highway, N.E. Mailstop K-10 Atlanta, GA 30341 [[alternative HTML

I am trying to install R on a SLED 10.1 machine. R-base-2.7.0-7.1-i586.rpm fails with stas at linux-6b8s:~/RPMs> rpm -Uvh R-base-2.7.0-7.1.i586.rpm warning: R-base-2.7.0-7.1.i586.rpm: Header V3 DSA signature: NOKEY, key ID 14ec5930 error: Failed dependencies: libgfortran.so.1 is needed by R-base-2.7.0-7.1.i586 I tried to trick it into believing there's the library by setting up

I'm trying to learn how to calibrate/postStratify/rake survey data in preparation for a large survey effort we're about to embark upon. As a working example, I have results from a small survey of ~650 respondents, ~90 response fields each. I'm trying to learn how to (properly?) apply the aforementioned functions. My data are from a bus on board survey. The expansion in the

Will R have more glitches on one operating system as opposed to another, or is it pretty much the same? robert

R has a very wide audience, clinical research, astronomy, psychology, and so on and so on. I would consider data analysis work to be three stages: data preparation, statistical analysis, and producing the report. This regards the process of getting the data ready for analysis and reporting, sometimes called "data cleaning" or "data munging" or "data wrangling". So as

Dear R users, I am trying to import a table from STATA, a dta file. With a table called "table", this is what I do : library("foreign") read.dta(table) It does not work. What am I doing wrong ? Best Regards, Dwayne [[alternative HTML version deleted]]

Dear R-Users, Is anyone aware of a significance test which allows demonstrating that one distribution dominates another? Let F(t) and G(t) be two distribution functions, the alternative hypothesis would be something like: F(t) >= G(t), for all t null hypothesis: F(t) < G(t), for some t. Best wishes, Matthias PS. This one would be ok, as well: F(t) > G(t), for all t null

Is it possible to fit a structural equation model with link functions in R? I am trying to build a logistic-regression-like model in sem, because incorporating the dichotomous variables linearly seems inappropriate. Mplus can do something similar by specifying a 'link' parameter, but I would like to be able to do it in R, ofcourse. I have explored the 'sem' package from John Fox,

Hi again, Typo in the last email. Should read "about 40 standard deviations". Jim On Thu, Nov 30, 2017 at 10:54 AM, Jim Lemon <drjimlemon at gmail.com> wrote: > Hi Robert, > People want different levels of automation in the software they use. > What concerns many of us is the desire for the function >

How difficult is it to get a good feel for the internals of R, if you want to learn the general code base, but also the CPU intensive stuff ( much of it in C or Fortran?) and the ways in which the general code and the CPU intensive stuff is connected together? R has a very large audience, but my understanding is that only a small group have a good understanding of the internals (and some of those

Hi Robert, People want different levels of automation in the software they use. What concerns many of us is the desire for the function "figure-out-what-this-data-is-import-it-and-get-rid-of-bad-values". Such users typically want something that justifies its use by being written by someone who seems to know what they're doing and lots of other people use it. One advantage of many R

I don't think my view is of interest to many, so offlist. I reject this: " I would consider data analysis work to be three stages: data preparation, statistical analysis, and producing the report." For example, there is no such thing as "outliers" -- data to be removed as part of cleaning/preparation -- without a statistical model to be an "outlier" **from**,

Hello, I am running polychoric correlations on a dataset composed of 12 ordinal and binary variables (N =384), using the polycor package. One of the association (between 2 dichotomous variables) is very high using the 2-step estimate (0.933 when polychoric run only between the two variables; but 0.801 when polychoric run on the 12 variables). The same correlation run with ML estimate returns a

1) What is easy for one person may be very hard for another, so your question is really unanswerable. You do need to know C and Fortran to get through the source code. Get started soon reading the R Internals document if it sounds interesting to you... you are bound to learn something even if you don't stick with it. If you have questions about the internals though, you should read the Posting

G'Day R users! Following an ordination using prcomp, I'd like to test which variables singnificantly contribute to a principal component. There is a method suggested by Peres-Neto and al. 2003. Ecology 84:2347-2363 called "bootstrapped eigenvector". It was asked for that in this forum in January 2005 by J?r?me Lema?tre: "1) Resample 1000 times with replacement entire

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

Dear list useRs, I have to generate a random set of coordinates (x,y) in [-1 ; 1]^2 for say, N points. At each of these points is drawn a circle (later on, an ellipse) of random size, as in: > N <- 100 > > positions <- matrix(rnorm(2 * N, mean = 0 , sd= 0.5), nrow=N) > sizes<-rnorm(N, mean = 0 , sd= 1) > plot(positions,type="p",cex=sizes) My problem is to

Dear all I have used the lda and predict functions to classify a set of objects of unknown origin. I would like to use a jackknife reclassification to assess the degree to which the outcomes deviate from that expected by chance. However, I can't find any function that allows me to do this. Any suggestions of how to generate the jackknife reclassification to assess classification accuracy?