search for: poststratify

Hi everyone, my apologies in advance if I'm overlooking something simple in this question. I am trying to use R's survey package to make a direct method age-adjustment to some complex survey data. I have played with postStratify, calibrate, rake, and simply multiplying the base weights by the correct proportions - nothing seems to hit the published numbers on the nose. I am trying to replicate any of the following: the stdize and stdweight parameters from a Stata complex survey analysis command (like this) s...

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

...rom a survey where household were interviewed. The sample has 4 criteria on which the stratification was based: REGION, SIZE OF HOUSEHOLD, SIZE OF LOCALITY, AGE OF HEAD OF HOUSEHOLD. Since i don't have the whole information in each cell of the cross region*sizehh*sizeloc*age i can't use the postStratify function from Survey package. Is that correct? (I think so but i need a competent answer) The only additional info that i have is the size of a cell from a 2*2 crossing (eg: I know the population size for all the strata defined by region*sizehh, region*sizeloc, sizeloc*age........) so i have...

...c("S1","S2"),c(5,3)), weight=rep(c(3,4),c(5,3)), nh=rep(c(5,3),c(5,3)), Nh=rep(c(15,12),c(5,3)), y=c(23,25,27,21,22, 77,72,74) ) pop.types <- table(stratum=age$stratum) age.post <- svydesign(ids=~1, strata=NULL, data=age, fpc=~Nh) ## no clusters, no strata post <- postStratify(design=age.post, strata=~stratum, population=pop.types) svymean (~y, post) svytotal (~y, post) gives mean SE y 42.625 0.5467 total SE y 341 4.3737 So, is it correct to define pop.types as the number of elements sampled per stratum (nh) or rather the total of elements per stra...

...egression 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 respondents). I would like to apply Rao's rescaling bootstrap procedure and poststratify the weights to population control totals in each bootstrap replicate. I know how to do all of this in Stata but have not yet seen any means of doing so in R. I presume I could do what is needed using batch processing but was hoping that there might be a way to pass the rq parameter estimates to...

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 fro...

First the R question. I have the results of a rather large survey (thousands of forms, each with dozens of questions) with some existing weights and expansion factors. I wish to add additional weighting factors, based on new information that elements of certain variables should appear in certain proportions. Where should I look in R to develop what is essentially an N-dimensional balancing

...00 1.333333 11.833333 14.000000 A8 0.000000 0.000000 0.000000 0.000000 5.800000 A9 0.000000 0.000000 0.000000 0.000000 31.000000 A10 0.000000 0.000000 0.000000 0.000000 47.250000 Me da el siguiente mensaje: * A Freq Pop.Freq* *3 A3 0 1* *Error en postStratify.survey.design(design, strata[[i]], population.margins[[i]], : * * Some strata absent from sample: use partial=TRUE to ignore them.* *¿Como puedo incluir partial=TRUE en el rake para que no me de error?* *Saludos,* *Sebastian.* [[alternative HTML version deleted]]