similar to: Quantile regression with complex survey data

Hi, there, I am using PC window version R and dealing with big dataset usually. May anyone let me whether the maximal dataset size in R is limited by computer memory or hard drive capacity? Thanks in advance. Yiling Cheng, M.D., Ph.D. Project Manager The Cooper Institute for Aerobics Research 12330 Preston Road, Dallas, Texas 75230 phone: (972) 3413248; Fax: (972) 3413224

Dear there, R is pretty flexible and powerful. I wonder whether there are any GUI programs to do basic statistic work by just clicking menu and selecting procedure. Thank you for your time. Yiling -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info",

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

what does R have to compare with , say , proc surveymeans, estimate survey means/proportions with standard errors, using Taylor methods? [[alternative HTML version deleted]]

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

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

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,

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

Dear R users, I have a large individual-level dataset (~700,000 records) which I am performing a conditional logistic regression on. Key variables include the dichotomous outcome, dichotomous exposure, and the stratum to which each person belongs. Using this individual-level dataset I can successfully use clogit to create the model I want. However reading this large .csv file into R and running

Dear Ladies and Gentlemen, I have a fairly large database (N=13,000) and a single main categorical discriminator between the groups. I want to look at the time course of a number of continuous biochemical variables over chronologic age. Therefore I believe I need to prepare hexbinplots in two columns with simple regression lines in them (with useOuterStrips (in library(latticeExtra) if

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

I am a physician examining an NHANES dataset available at the NCHS website: http://www.cdc.gov/nchs/about/major/nhanes/nhanes2005-2006/demo_d.xpt http://www.cdc.gov/nchs/about/major/nhanes/nhanes2005-2006/hdl_d.xpt http://www.cdc.gov/nchs/about/major/nhanes/nhanes2005-2006/tchol_d.xpt Thank you to the R authors and the foreign package authors in particular. Importing from the SAS export

Dear all, One of my friends asked me if it is possible to extract actual R function arguments literally (precisely, as strings). The reason is simple. He feels sometimes awkward to attach quotation marks :-). What he actually wants is to pass R command arguments to XLisp subroutines (He has been an enthusiastic XLisp user for a long time and still tends to use R as a wrapper to XLisp). Is it

Hello All, I am still a beginner with R, and I only have a week or two under my belt so far. I'm working with NHANES anthropometric data on stature. I have two sets of data that have different statistical weights. I'm trying to combine those two data sets into one "mega-set" while retaining each data point's individual weight. If you have any idea as to how this is

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

We are constructing growth charts (age/weight and age/length) for children with diagnosis that impacts weight/length. But we we don't know how to use R for producing growth charts. We are collection data of Age, Weight and Length. The data are used to produce diagnosis-specific Growth charts (like the CDC Growth Charts:

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

I did some serach around. It seems that ROC curve computation is not supported on R. Anyone has some leads? Thanks. Jason ===== Jason G. Liao, Ph.D. Division of Biometrics UMDNJ School of Public Health 335 George Street, Suite 2200 New Brunswick, NJ 08903-2688 phone (732) 235-9748, fax (732) 235-9777 http://www.geocities.com/jg_liao __________________________________________________ Great

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