search for: svymean

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 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 0.014060 2.8561 W525131 0.805421 0.015425 3.1350 W525033 0.242982 0.020074 4.5239 W525163 0.904647 0.013905 4.6289 W525165...

..., 23,25,27,21,22, 33,27,29), ncol=6, byrow=F) colnames(age)<-c("stratum", "id", "weight", "nh", "Nh", "y") age<-as.data.frame(age) ## create survey design object age.des1<-svydesign(ids=~id, strata=~stratum, weight=~Nh, data=age) svymean(~y, age.des1) ## gives mean 25.568, SE 0.9257 age.des2<-svydesign(ids=~id, strata=~stratum, weight=~I(nh/Nh), data=age) svymean(~y, age.des2) ## gives mean 25.483, SE 0.9227 age.des3<-svydesign(ids=~id, strata=~stratum, weight=~weight, data=age) svymean(~y, age.des3) ## gives mean 26.296, S...

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 work...

Hello, Although my R code for the svymean () and svyquantile () functions works fine, I am stuck with the svyby () and make.formula () functions. I got the following error messages. - Error: object of type 'closure' is not subsettable # svyby () - Error in xx[[1]] : subscript out of bounds # make.formula () A repr...

...ell me what the structure has to be for a stratified sample with clustering? Looking at the code, it appears to me that it does not allow more than 1 observation per psu [i.e. any(sc > 1)]. Error 2). If I go ahead and specify check.strata=FALSE, then svydesign runs ok. I then tried using the svymean function. In the following example, if I specify na.rm=TRUE, I get the error below: > svymean(nhis.df$crc10yr, design=nhis.design, na.rm=TRUE) Error in rowsum.default(x, strata) : Incorrect length for 'group' I traced this to the svyCprod call within svymean. SvyCprod calls rowsum a...

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?

Using the survey package I find it is convenient and easy to get estimated proportions using svymean, and their corresponding estimated standard errors. But is there any elegant/simple way to calculate corresponding confidence intervals for those proportions? Of course +/- 1.96 s.e. is a reasonable approximation for a 95% CI, but (incorrectly) assumes symmetrical distribution for a proportion....

...I fix this problem? I have used aggregate with "mean" and "weighted.mean", and that works fine. I am trying to find out where the difference is. What would be an efficient alternative to aggregate for a large dataset? > s <- aggregate(income,list(age,sex),function(x) (svymean(~x,design=d.na))) Error in aggregate(income, list(age, sex), function(x) (svymean(~x, : Object "income" not found [[alternative HTML version deleted]]

...2001 17623 2122 ... Note some years are missing - they are part of the dataset, but all responses are NA (the question wasn't asked). However, this gives an error, and I'd like to understand why - it works for variables without missing years: svyby(~problem.vandal, ~SurvYear, seh.dsn, svymean, na.rm=TRUE) Error in tapply(1:NROW(x), list(factor(strata)), function(index) { : arguments must have same length The error only occurs when na.rm=TRUE and there are no observations in one year. Thanks alex Please access the attached hyperlink for an important electronic communications discla...

...am astonished because it does not seem to do things that are easy to do on other softs. I have got data with missing values (I am working on a questionnaire filled by students) and with weights and stratification. I learned how to use the survey package, and I would like to do an average (by using svymean) of a variable that has some NA. I first tried : svymean(~q135,survey) #q135 is the name of the variable and survey is the name of the survey design but as there is missing values, i get that : mean SE q135 NA NA as a consequence I put the observations without missing values in a vector x...

...mpling design: library(survey) multi3 <- data.frame(cluster=c(1,1,1,1 ,2,2,2, 3,3), id=c(1,2,3,4, 1,2,3, 1,2), nl=c(4,4,4,4, 3,3,3, 2,2), Nl=c(100,100,100,100, 50,50,50, 75,75), M=rep(23,9), y=c(23,33,77,25, 35,74,27, 37,72) ) dmulti3 <- svydesign(id=~cluster+id, fpc=~M+Nl, data=multi3) svymean (~y, dmulti3) mean SE y 45.796 5.5483 svytotal(~y, dmulti3) total SE y 78999 13643 and I estimate the population total as N=M/m sum(Nl) = 23/3*(100+50+75)=1725. With this, my variance estimator is: y1<-mean(multi3$y[1:4]) # 39.5 y2<-mean(multi3$y[5:7]) # 45.33 y3<-mean(mult...

...id = ~SDMVPSU , strata = ~SDMVSTRA , nest = TRUE , weights = ~WTMEC2YR , data = x ) # only perform analyses among individuals aged 20 and over z <- subset( y , RIDAGEYR >= 20 ) # these four commands calculate the correct non-age-adjusted estimate svymean( ~HI_CHOL , z , na.rm = T ) svyby( ~HI_CHOL , ~race , z , svymean , na.rm = T ) svyby( ~HI_CHOL , ~RIAGENDR , z , svymean , na.rm = T ) svyby( ~HI_CHOL , ~RIAGENDR+race , z , svymean , na.rm = T ) # but matching the figure exactly requires an exact age adjustment. # create the population types vec...

Hi all, When I try the following with pkg Survey it returns the error below: ftable(svyby(~INCOME, ~AGECL+RACECL, svymean, design=q50), rownames=list(AGECL=c("<35", "35-44", "45-54", "55-64", "65-74", ">=75"), RACECL=c("white non hispanic", "non white or hispanic")) Erro...

...he replicates estimates from a crosstab done using svyby? Here is an example from the help page for svyby in the package: > data(api) > dclus1<-svydesign(id=~dnum, weights=~pw, data=apiclus1, fpc=~fpc) > rclus1<-as.svrepdesign(dclus1) > > a <- svyby(~api99, ~stype, rclus1, svymean, return.replicates=TRUE) > a$replicates NULL But, compare to > b <- svymean(~api99, design=rclus1, return.replicates=TRUE) > b$replicates [1] 606.8488 611.5866 609.1989 605.5765 608.1381 606.6927 609.8101 599.4371 602.4368 601.8792 606.7531 630.6575 600.1882 607.5549 599.9942 > T...

...om those obtained from svytotal. The estimated mean incomes do agree with each other. It seems that using the na.rm option with svytotal is the same as replacing the missing values with zero's, which is not what I would have expected, especially since this behaviour seems to differ from that of svymean. Is there a reason for this behaviour? I can of course remove the missing values myself before creating the survey object. However, with many different variables with different missing values, this is not very practical. Is there an easy way to get the behaviour I want? Thanks for your help. Wit...

...mple size p1=the proportion from the second sample n2=the second sample size 2. How can i find the median of a variable in survey package? a<-c(1:10) b<-sample(1:20, 10, replace=T) b1<-sample(0:1, 10, replace=T) c<-data.frame(a,b, b1) library(survey) design<-svydesign(id=~1, data=c) svymean(~b, design) svymean gives me the mean, but what function gives me the svymedian, and what function gives me the svyproportion for b1? I want to know the median for a metric variable and the proportion for a binomial variable ? 3. Could time series analysis (arima/arma) be applied on data that...

...pled. y are the values sampled. This is my example data: clus1 <- data.frame(cluster=c(1,1,1,2,2,2,3,3,3), id=seq(1:3,3), weight=rep(72/9,9), nl=rep(3,9), Nl=rep(3,9), N=rep(72,9), y=c(23,33,77, 25,35,74, 27,37,72) ) 1. Let M=m=3 and N=n=9. Then: dclus1<-svydesign(id=~cluster, data=clus1) svymean(~y, dclus1) mean SE y 44.778 0.294, the unweighted mean, assuming equal probability in the clusters. ok. 2. Let M=23, m=3 and N=72, n=9, then I am unable to use svydesign correctly: dclus2<-svydesign(id=~cluster, data=clus1, fpc=~N) svymean(~y, dclus2) mean SE y 44.778 0.28...

...AGECL = factor( AGECL ) , RACECL = factor( RACECL ) ) On Sun, Jul 9, 2017 at 2:59 PM, Orsola Costantini via R-help < r-help at r-project.org> wrote: > Hi all, > > When I try the following with pkg Survey it returns the error below: > > ftable(svyby(~INCOME, ~AGECL+RACECL, svymean, design=q50), > rownames=list(AGECL=c("<35", "35-44", "45-54", "55-64", > "65-74", ">=75"), > RACECL=c("white non hispanic", "non white or hispani...

...Mean Std. Err. [95% Conf. Interval] -------------+------------------------------------------------ ell0 | .0218579 .0226225 -.0266624 .0703783 -------------------------------------------------------------- # R x64 # simple example using example code pulled from ?svymean options(digits=20) library(survey) library(foreign) # read the data file from a website, to make sure you're using the same data in both R and stata x <- read.dta( "http://www.ats.ucla.edu/stat/stata/library/apiclus1.dta" ) dclus1<-svydesign(id=~dnum, fpc=~fpc, data=x) # mean...