search for: pweight

...ne 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 NAMCS describes this for Stata as follows (note the variable names in the data are in caps): The pweight (PATWT), strata (CSTRATM), and PSU (CPSUM) are set with the svyset command as follows: svyset pweight PATWT svyset strata CSTRATM svyset psu CPSUM They provide similar instructions for SUDAAN: as SUDAAN 1-stage WR Option The program below provides a with replacement ultimate cluster (1-stage) est...

Hi: I have usually used the GROWTH() excel function to do this but now want to see if I can do this with R. I want to predict values into the future, possibly with the predict.arima Function. I have the following weekly fish weight averages: weight <- c("2.1","2.4","2.8","3.6","4.1","5.2","6.3") week <-

...weighted survey sample. polr permits case weights with the "weights" option, but I cannot figure out from existing documentation what it actually does with these weights. I'm concerned about this because I get somewhat different results using Stata's ologit command with the pweights option and very different results using proc logistic in SAS with its weight option. So my basic question is whether or not it is appropriate to use the weight option for polr with my data. Best, Greg ............................................................. Gregory Wawro...

Is anyone familiar with a way to account for sampling weights (e.g., in order to cope with selection bias) for individual respondents using the bayesm package (e.g., rhierMnlRwMixture)? In the regular MNL this can easily be done in STATA using the mlogit function with pweights option. However, I am unfamiliar with a way to do it in HB estimation. Any help or hints are appreciated. Best, Klaus -- View this message in context: http://r.789695.n4.nabble.com/Sampling-Weights-in-HB-Choice-Modelling-e-g-rhierMnlRwMixture-tp3407486p3407486.html Sent from the R help mailin...

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,