search for: nhis

....510514 0 2 2 339 1429.5963 1" newdata <- read.table (textConnection(xd1), header=TRUE, as.is=TRUE) dim (newdata) # make the grouping variable (xspd)2 newdata$xspd2 <- factor(newdata$xspd2,levels=c (1,2),labels=c('SPD', 'No SPD'), ordered=TRUE) nhis <- svydesign (id=~psu,strat=~stratum, weights=~wt8, data=newdata, nest=TRUE) # mean age at death - nationwide svymean( ~dthage, data=nhis , subset (nhis, mortstat==1)) # mean by SPD status svyby(~dthage, ~xspd2 , design=nhis, svymean ) #percentile svyquantile(~dthage, data = nhis , sub...

Hi, I have been experimenting with the new Survey package. Specifically, I was trying to use some of the functions on the public-use survey data from NHIS (2000 Sample Adult file). Error 1): The first error I get is when I try to specify the complex survey design. nhis.design<-svydesign(ids=~psu, probs=~probs, strata=~strata, data=nhis.df, check.strata=TRUE) Error in svydesign(ids = ~psu, probs = ~probs, strata = ~strata, data = nhis.df, :...

...RUE) # Grouping variable "xsmoke" must be a factor tor$xsmoke <- factor(tor$xsmoke,levels=c (1,2,3), labels=c('Current SMK','Former SMK', 'Never Smk'), ordered=TRUE) is.factor(tor$xsmoke) # object with survey design variables and data nhis <- svydesign (id=~psu,strat=~stratum, weights=~wt8, data=tor, nest=TRUE) MyBreaks <- c(18, 25, 35, 45, 55, 65, 75, 85) par(mfrow=c(2,2)) #Chart 1 options( survey.lonely.psu = "adjust" ) svyhist (~age_p, subset (nhis, xsmoke=='Current SMK'), breaks=MyBreaks,...

...= No) educ Education Recode (1 = HS, GED, or less, 5 = some college, 6 = Bachelor's or AA degree, 9 = Master's & higher Here are 2 calls to tree and a snip of summary results: ### Use a sample of 100 #### > set.seed(331) > nsize = 100 > sam <- sample(1:nrow(nhis), nsize) > > t1 <- tree( RESP ~ AGE_P + ORIGIN_I + RACRECI2 + parents + educ, + method = "class", + control = tree.control(nobs = nsize, minsize = 10), + data = nhis[sam,]) > summary(t1) Classification tree: tree(formula = RESP ~ AGE_P + ORIGIN_I + RACREC...

...39;, as.is=TRUE) # Grouping variable (xspd) to be factor tor <- within(tor, { xspd2 <- factor(xspd2,levels=c (1,2), labels=c('SPD', 'No SPD'), ordered=TRUE) } ) # object with survey design variables and data nhis <- svydesign (id=~psu,strat=~stratum, weights=~wt8, data=tor, nest=TRUE) MyBreaks <- c(18,35,45,55,65,75,85,95) png("svyhist_age_at_death.png") svyhist (~dthage, subset (nhis, xspd2==2), breaks=MyBreaks, main= " ", col="grey80",...

...t 5 or 6 by now) I get the following Microsoft error message and the R-Console crashes. R for Windows GUI front-end has encountered a problem and needs to close. We are sorry for the inconvenience. I would greatly appreciate help with this as we need to use R to estimate confidence intervals for NHIS data, and our deliverable is due this week. Thanks in advance.

Hi, is there a way to analyze subpopulations (e.g. women over 50, those who answered "yes" to a particular question) in a survey using Survey package? Other packages (e.g. Stata, SUDAAN) do this with a subpopulation option to identify the subpopulation for which the analysis shoud be done. I did not see this option in the Survey package. Is there another way to do this?

Sorry for the lack of reproducible data, but this seems to be a problem inherent to my dataset and I can't figure out where the issue is. I have several data frames set up as a time series with identical POSIXct date formats. If I keep the original data in data frame format and merge them using base merge- everything is perfect and everyone is happy. If I transform the data frames to zoo

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