similar to: large survey data set

Hi, I am new to R, coming from a few years using Stata. I've been twisting my brain and checking several R and S references over the last few days to try to solve this data management problem: I have a data set with a unique patient identifier that is repeated along multiple rows, a variable with month of patient encounter, and a continous variable for cost of individual encounters. The data

Hello, How I use the function as.svrepdesign without memory.size problems? desenho_npc_JK <- as.svrepdesign(desenho_npc,type="JKn") Error: cannot allocate vector of size 161.3 Mb In addition: Warning messages: 1: Reached total allocation of 1022Mb: see help(memory.size) 2: Reached total allocation of 1022Mb: see help(memory.size) 3: Reached total allocation of 1022Mb:

Good afternoon! I'm trying to use the Survey package for a stratified sample which has 4 criteria on which the stratification is based. I would like to get the corrected weights and for every element i get a weight of 1 E.g: tipping design <- svydesign (id=~1, strata= ~regiune + size_loc + age_rec_hhh + size_hh, data= tabel) and then weights(design) gives

Dear WizaRds, Working through sampling theory, I tried to comprehend the concept of stratification and apply it with Survey to a small example. My question is more of theoretic nature, so I apologize if this does not fully fit this board's intention, but I have come to a complete stop in my efforts and need an expert to help me along. Please help: age<-matrix(c(rep(1,5), rep(2,3),

https://gist.github.com/rpietro/6430771 stemDocument function doesn't seem to be working. Tried to look up and a few people have reported the problem, but no solution that I could find. would appreciate any help

Good afternoon! I'm trying to use the survey package to get a better point of view for my data, but i need some piece of advice: i have some data from a survey which has been stratified using 2 criteria: region(7 values), size of locality(5 values) Using the survey pakage how can i define in a correct way this design (taking into account all 4 strata not just one as in the Survey

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 =

Hi dears, I expect that Mr Thomas Lumley will read this message. I have data from a complexe stratified survey. The population is divide in 12 regions and a region consist to and urban area and rural one. there to region just with urbain area. stratification variable is a combinaison of region and area type (urban/rural) In rural area, subdivision are sample with probabilties proporionnal to

Howdy, Referencing the below exchange: https://stat.ethz.ch/pipermail/r-help/2006-April/103862.html I am still getting the same warning ("non-integer #successes in a binomial glm!") when using svyglm:::survey. Using the API data: library(survey) data(api) #stratified sample dstrat<-svydesign(id=~1,strata=~stype, weights=~pw, data=apistrat, fpc=~fpc)

Hi, I'm trying to get standard errors for some of the variables in my data frame. One of the questions on my survey is whether faculty coordinate across curriculum to include Arts Education as subject matter. All the responses are coded in zeros and ones obviously. For some of the other variables I have a 2 for those that responded with "Don't Know". I'm getting NA for

I have the final sample weight (expansion factor) from a socieconomic survey. I don't know the exact design used in the study ( (probably is a stratified two-stage design). To illustrate my problem I will use the next dataset which have a sample weight (but the design is not specified) and incorporate the design with svydesign and create some bootstrap replicates in order to be able to

Dear list, I got some surprising results when using the svytotal routine from the survey package with data containing missing values. Some example code demonstrating the behaviour is included below. I have a stratified sampling design where I want to estimate the total income. In some strata some of the incomes are missing. I want to ignore these missing incomes. I would have expected that

hi, probably not.. if your survey dataset has a complex design (like clusters/strata), you need to include them in the `svydesign` call. coercing an incorrect survey design into a replicate-weighted design will not fix the problem of failing to account for the sampling strategy On Mon, Apr 4, 2016 at 12:01 AM, Jos? Fernando Zea <jfzeac at gmail.com> wrote: > I have the final sample

Dear R-help, Let me know if I should email r-devel instead of this list. This message is addressed to Professor Lumley or anyone familiar with the survey package. Does svycoxph() implement the method outlined in Binder 1992 as referenced in the help file? That is, are weights incorporated in the ratio term (numerator and denominator) of the estimating equation? I don't believe so since

Hi, I found a discrepancy between results in R and Stata for a factor analysis with a promax rotation. For Stata: . *rotate, factor(2) promax* (promax rotation) Rotated Factor Loadings Variable | 1 2 Uniqueness -------------+-------------------------------- pfq_amanag~y | -0.17802 0.64161 0.70698 pfq_bwalk_~ø | 0.72569 0.05570

Dear WizaRds, having met some of you in person in Vienna, I think even more fondly of this community and hope to continue on this route. It was great talking with you and learning from you. Thank you. I am trying to work through an artificial example in post stratification. This is my dataset: library(survey) age <- data.frame(id=1:8, stratum=rep(

Hello, all. I wanted to use the "survey" package to analyze data from the National Ambulatory Medical Care Survey, and am having some difficulty translating the analysis keywords from one package (Stata) to the other (R). The data were collected using a multistage probability sampling, and there are variables included to identify the sampling units and weights. Documentation from the

Hello, I am analyzing the results of a survey of the student body on the use of certain technologies. The student body was divided in strata according to two criteria, college and user class. The resulting 24 strata were sampled. Subjects filled out a survey with a number of questions, most of them of the yes-no variety. I created a data.frame with the results for the survey. One row for

Dear all, We are analysing some survey data and we are not sure if we are using the correct syntax for our design. The population of interest is a set of 4416 polygons with different sizes ranging from 0.003 to 45.6 ha, 7460 ha in total. Each polygon has a binary attribute (presence/absence) and we want to estimate the probability of presence in the population. We used sampling with replacement

To whom it may concern, I have a question referring to the calculation of variance estimation of the survey package I need to estimate the variance for different Domains but for a stratified sampling desing in several stages. Särndal et al (1992), CAP 10, makes reference to this problem. My question is if it is possible by means of "survey package" to obtain these