similar to: Combining Data Sets w/ Weights

Hi, I'm analysing some anthropometric data on fifty odd skull bases. We know the gender of each skull, and we are trying to develop a predictor to identify the sex of unknown skulls. Rpart with cross-validation produces two models - one of which predicts gender for Males well, and Females poorly, and the other does the opposite (Females well, and Males poorly). In both cases the error

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 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

Hi, I was wondering if there is a ready made function or parameter for indicating the sample size in boxplots? Here's what I came up with so far: library(ISwR) data(energy) attach(energy) boxplot(expend~stature) sample.size <- tapply(expend, stature, length) sample.size <- paste("N=", sample.size, sep="") mtext(sample.size, at=1:length(unique(stature)), line=2,

# Get mean, min, max sigma and skew by group options (digits = 3) library (ISwR data(energy) data %>% group_by(stature) %>% summarize( Mean = mean(expend), Min = min(expend), Max = max(expend), Sigma = sd(expend), Skew = skew(expend)) # Output stature Mean Min Max Sigma Skew <fct> <dbl> <dbl> <dbl> <dbl> <dbl> 1

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

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:

> On Apr 14, 2018, at 12:18 PM, WRAY NICHOLAS via R-help <r-help at r-project.org> wrote: > > > -------- Original Message ---------- > From: WRAY NICHOLAS <nicholas.wray at ntlworld.com> > To: peter dalgaard <pdalgd at gmail.com> > Date: 14 April 2018 at 20:18 > Subject: Re: [R] Reading xpt files into R > > > Well yesterday I'd downloaded

Dear folks ? I have a large (26 gig) ASCII flat file in fixed-width format with about 10 million observations of roughly 400 variables. (It is 51 years of Current Population Survey micro data from IPUMS, roughly half the fields for each record). The file was produced by automatic process in response to a data request of mine. The file is not accompanied by a human-readable file giving the

Dear all, the dataset documented under ?crimtab was also used in: @article{TreloarAE1934, title = {The adequacy of "{S}tudent's" criterion of deviations in small sample means}, author = {Treloar, A.E. and Wilder, M.A.}, journal = {The Annals of Mathematical Statistics}, volume = {5}, pages = {324-341}, year = {1934} } The following is

Hello I would like to pass a model formula as an argument to the with.mids function from the mice package. The with.mids functon fits models to multiply imputed data sets. Here's a simple example library(mice) #Create multiple imputations on the nhanes data contained in the mice package. imp <- mice(nahnes) #Fitting a linear model with each imputed data set the regular way works

Hello, I'm using a complex survey dataset and my goal is to simply spit out a bunch of probability-weighted outcome variable means for the different levels of covariate. So I first define the structure of the study design (I'm using the CDC's NHANES data): dhanes <- svydesign(id=~PSU, strat=~STRATA, weight=~lab_weight, data=final, nest=TRUE) No problem there. Now I use the

Dear Niels I am trying to construct some anthropometric standards for adults using LMS and GAMLSS in R. I saw that you had a problem that I have with the package lmsqreg of the package being reported as "not a valid package". I presume you solved your problem, but I did not see how in the r-help list. Can you help? Thanks, Richard Palmer-Jones [[alternative HTML version

ibuae~kundgebungrequestinfo computergphone' am-,er''ica d`r`^ugs & 0v^ernig~'ht d'e_,liver~ optimgdasyatidae http://www.morning-meds.com At this announcement Rob began to quiver with excitement, and sat staring eagerly at the Demon, while the latter increased in stature and sparkled and glowed more brilliantly than ever -----Original Message----- From: Mica

-------- Original Message ---------- From: WRAY NICHOLAS <nicholas.wray at ntlworld.com> To: peter dalgaard <pdalgd at gmail.com> Date: 14 April 2018 at 20:18 Subject: Re: [R] Reading xpt files into R Well yesterday I'd downloaded the "foreign" package and tried to open the xpt file using that: library(foreign) read.xport("test.xpt") I got the following

hello, I am trying to do exploratory factor analysis with BRFSS dataset ( http://www.cdc.gov/brfss/technical_infodata/surveydata/2008.htm) for a couple of days, but I was not able to do that and got frustrated. Can anybody help me with step by step guide? BRFSS dataset provides ASCII or SAS format. Thank you. chloe [[alternative HTML version deleted]]

What's the consensus? Should winbind even be considered for production use? Looking back through the archives of the Samba lists, there's a lot of doubt about it. Where people have had problems, there are more often than not no solutions given. When I look at the man page in 3.0.28, there are litterally blank spots awaiting completion, and lack of documentation of sometimes-essential

Hi, I'm having trouble sweaving the following example: --8<------------------------schnipp------------------------->8--- \documentclass{article} \begin{document} \SweaveOpts{echo=FALSE} @ <<>>= rm(list=c(ls())) library(Hmisc) library(ISwR) data(energy) energy$log <- log(energy$expend) attach(energy) @ %def @ <<results=tex>>= mysum <- summary(stature ~

With the release of our filmfury.com project, I''ve been trying to rise to the stature of a true system administrator in the last couple of days (haha). I''m trying to understand how all of the pieces to this apache/fastcgi deployment fit together. Here''s what I''ve learned so far: * You need a separate FastCGI server for each Rails application on your

Dear All, I try to read the SAS transport file in R, but it shows error. Please help! I am using R 2.11.1 library(foreign) download.file("http://isites.harvard.edu/fs/docs/icb.topic35387.files/demo_c.xpt","C:/Desktop/demo_c.xpt") sasxport <- read.xport("C:/Desktop/demo_c.xpt") Error in lookup.xport(file) : file not in SAS transfer format -- View this