similar to: Memory Problems with CSV and Survey Objects

Greetings, I am revisiting code from several different files I have saved from the past and all used to run flawlessly; now when I run any of the svyglm related functions, I am coming up with an error: Error in model.frame.default(formula = F3ATTAINB ~ F1PARED, data = data, : the ... list does not contain 4 elements The following is a minimal reproducible example: library(RCurl)

Is there a way to create a BRR svrepdesign from a survey design when the number of PSUs is odd in one or more stratum? Creating a JKn svrepdesign with that condition works okay, but when I tried to create a svrepdesign with type="BRR" I get an error and this message: "Can't split with odd numbers of PSUs in a stratum" I get that message when I tell it to merge the

hi, i am not hitting an error when i copy and paste your code into a fresh console. maybe compare your sessionInfo() to mine? > sessionInfo() R version 3.4.1 (2017-06-30) Platform: x86_64-w64-mingw32/x64 (64-bit) Running under: Windows Server 2008 R2 x64 (build 7601) Service Pack 1 Matrix products: default locale: [1] LC_COLLATE=English_United States.1252

NOTE: posted this to gluster-devel when I meant to post it to gluster-users 01 | 02 mirrored --| 03 | 04 mirrored --| distributed 05 | 06 mirrored --| 1) Would this command work for that? glusterfs-volgen --name repstore1 --raid 1 clustr-01:/mnt/data01 clustr-02:/mnt/data01 --raid 1 clustr-03:/mnt/data01 clustr-04:/mnt/data01 --raid 1 clustr-05:/mnt/data01 clustr-06:/mnt/data01 So the

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:

*Hola!!! resulta que tengo unos datos de divisas ordenados por fechas (días) los que he convertido a formato tipo YYYY-MM-DD donde DD siempre es 01:* * * * EUR.resto$date<-as.Date(EUR.resto$date) EUR.resto$mo <- substr(EUR.resto$date,6,7) EUR.resto$yr <- substr(EUR.resto$date, 1,4)

Hello, Is there a way to get complex sample variances in the survey package on summary statistics other than means? If not, can they be added to a future version? It would be be great to have them on totals, quantiles, ratios, and tables (eg row percent, columns percent, etc). Thanks. Fred --------------------------------- [[alternative HTML version deleted]]

Afternoon R help, I want to run Rasch/IRT analyses using the ltm package, however, I am using large scale survey data which requires weighting for accurate results. I attempted to create a weighted object to insert into the formulae of the ltm packages, however, the survey data only includes 30 replicate weights and a sampling weight. The svrepdesign requires additional information such as

Hi all, I am using quantile regression with svy design. I want to retrieve summary regression statistics (std error, p-value), since I don't have any in my output: Commands: clus1_d<- svydesign(id=~cd002_co, weights=~wtper, strata=~str, data=data) bclus1<-as.svrepdesign(clus1_d,type="bootstrap",replicates=100) fit1<-

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

I am new to R and am interested in using the program to fit quantile regression models to data collected from a multi-stage probability sample of the US population. The quantile regression package, rq, can accommodate person weights. However, it is not clear to me that boot.rq is appropriate for use with multi-stage samples (i.e., is capable of sampling primary sampling units instead of survey

If I wanted to fit a logit model and account for clustering of observations, I would do something like: library(Design) f <- lrm(Y1 ~ X1 + X2, x=TRUE, y=TRUE, data=d) g <- robcov(f, d$st.year) What would I do if I wanted to do the same thing with a probit model? ?robcov says the input model must come from the Design package, but the Design package appears not to do probit? Thanks very

A video game has several short sound effects, many of them 0.1 to 0.5 seconds in length. Which lossy audio codec is most efficient for encoding waveforms this short? I'm working on an audio framework to replace SDL_mixer, which I didn't find as flexible as I'd like. I wrote a RIFF WAVE loader, a Vorbis file loader, and a streaming Vorbis file player. But when encoding samples for

How do I retrieve the 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

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

Hi, I am trying to fit a model with an ordered response variable (3 levels) and 13 predictor variables. The sample has complex survey design and I've used 'svydesign' command from the survey package to specify the sampling design. After reading the manual of 'svyglm' command, I've found that you can fit a logistic regression (binary response variable) by specifying the

Hello all, I am using AddHealth data to fit a cure, aka split population model using nltm. I am not sure how to account for the complex survey design - does anyone have any suggestions? Any help would be greatly appreciated! Sincerely, Sam

Hello everyone! I am analyzing a public use dataset which has both basic weights and replicated weights. I have found that only Stata seems to work with replicate weights but I would rather use R. Does anyone know if R can use replicate weights? If this is possible, could someone share some links and/or code for performing this action. Thank you for your time. Samantha Tornello, M.A. University

I have a distributed/replicated setup with Glusterfs 3.0.2, that I'm testing on 4 servers, each with access to /mnt/gluster (which consists of all directories /mnt/data01 - data24) on each server. I'm using configs I built from volgen, but every time I access a file (via an 'ls -l') for the first time, I get all of these messages in my logs on each server: [2010-05-04 10:50:30] W

To anyone who can help, I have two stupid questions, and one fairly intelligent question Stupid question (1): is there an R function to calculate a factorial of a number? That is...is there a function g(.) such that g(3) = 6, g(4) = 24, g(6) = 720, etc? Stupid question (2): how do you extract the estimated covariance matrix of the random effects in an lme object? Intelligent question