similar to: Survey analysis of repeated relationships?

Hello everybody I don't understand how I'm supposed to use svydesign caracteristics to explain to R that my sampling design is the following one Data base = tab1 here are the five first rows of the database (nrow = 11792) num esp Quarters Totcat Totshp Totgt Tbtpos fpc1 Totanim Id_An 10 2045 G

-------------------------------------------------- From: "Ahoussou Sylvie" <sylvie.ahoussou at antilles.inra.fr> Sent: Friday, September 12, 2008 9:48 AM To: "Thomas Lumley" <tlumley at u.washington.edu> Subject: Re: [R] Complex sampling survey _ Use of survey package > Thanks for your answer > > I think I made a mistake when I recopied the 5 first rows of

Dear all, I'm working on a design with rotating panels. Each site is sampled every X year. Have a look at the code below the get an idea of the design. In reality the number of sites will be (much) higher. However I'm not sure if I coded the design correctly in svydesign(). Can someone confirm that it is either correct or wrong? I've added the lmer() equivalent that I want to

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

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),

Version 3.9 of the survey package is now on CRAN. Since the last announcement (version 3.6-11, about a year ago) the main changes are - Database-backed survey objects: the data can live in a SQLite (or other DBI-compatible) database and be loaded as needed. - Ordinal logistic regression - Support for the 'mitools' package and multiply-imputed data - Conditioning plots,

Version 3.9 of the survey package is now on CRAN. Since the last announcement (version 3.6-11, about a year ago) the main changes are - Database-backed survey objects: the data can live in a SQLite (or other DBI-compatible) database and be loaded as needed. - Ordinal logistic regression - Support for the 'mitools' package and multiply-imputed data - Conditioning plots,

I have survey data that I am working on. I need to make some multi-way tables and regression analyses on the data. After attaching the data, this is the code I use for tables for four variables (sweight is the weight variable): > a <- xtabs(sweight~research.area + gender + a2n2 + age) > tmp <- ftable(a) Is this correct? I don't think I need to use the strata and cluster

Dear WizaRds, I am struggling with the use of twophase in package survey. My goal is to compute a simple example in two phase sampling: phase 1: I sample n1=1000 circuit boards and find 80 non functional phase 2: Given the n1=1000 sample I sample n2=100 and find 15 non functional. Let's say, phase 2 shows this result together with phase 1: ...................phase1........

Dear WizaRds, I am struggling to compute correctly a cluster sampling design. I want to do one stage clustering with different parametric changes: Let M be the total number of clusters in the population, and m the number sampled. Let N be the total of elements in the population and n the number sampled. y are the values sampled. This is my example data: clus1 <-

I am trying to perform cluster analysis on survey data where each respondent has answered several questions, some of which have categorical answers ("blue" "pink" "green" etc) and some of which have scale answers (rating from 1 to 10 etc).My problem is that certain age groups were over-sampled and I need to weight the data collected in order to accurately reflect the

This message is for those familiar with the survey package. I need to fit a weighted Cox model to accommodate the sampling weights as I have a case-control study with controls sampled at random from a database in a ratio 2:1 to cases (whom were all sampled). I want to make sure I am using the right svydesign syntax to specify this sampling design. Can anyone please check if the statement below is

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

Hi, we've upgraded recently from samba 3.0.23 to 3.0.25b. Since then, we've getting these error messages from winbindd: Jul 17 12:00:23 cvk027 winbindd[20772]: [2007/07/17 12:00:23, 0] lib/util_str.c:safe_strcpy_fn(659) The volume of these messages is very high, many times together with unreadable character garbage. Is there any way to correct or suppress these messages? Our

Hi, I'm trying to create a boxplot from the summary of a large data set and I'm having trouble finding any way to do this. I'm familiar with, but by no means good at, using R, so the only two websites I've found pertaining to this issue have been way over my head. I was hoping for a simple set of instructions that I could follow to produce a boxplot, in R, for three groups of

R experts, Hello, I am trying to sample a vector 1:40 without replacement such that no element in the new vector is within 7 units of either of its immediate neighbors. This is part of a larger program I am working on. The following code works well about 65 % of the time (14/40). The problem I encounter happens when the last element remaining to be sampled from the vector STRATA is within 7

Hello, I'm using the package survey, version 3.22-2 in R 2.11.1, on windows XP, but this isn't a platform issue. I am trying to calculate some regression and probability proportional to size (pps) estimates for a dataset I have. The data has 2 strata, weights, and cluster IDs. However, I can't find a way to use multiple strata in the svydesign function. Currently, I'm ditching

Dear Helpers   I have a sample frame and i have sampled from it using three methods and now i want to calculate the statistics but i only get the population parameters.   H <- matrix(rnorm(100, mean=50000, sd=5000)) sampleframe=data.frame(type=c(rep("H",100)),value=c(H)) sampleframe   str=strata(sampleframe,c("type"),size=c(20,), method="srswor")

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

I've been using strata(sampling) and found that if the dataframe to be sampled ("data") consists of repeated measures that are not sorted in order the run will fail on a given stratum. Ordering the dataframe prior to using strata() eliminates this problem. Thanks, Eric -- Eric Vander Wal Ph.D. Candidate University of Saskatchewan, Department of Biology, 112 Science Place,