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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

G'Day R users! Following an ordination using prcomp, I'd like to test which variables singnificantly contribute to a principal component. There is a method suggested by Peres-Neto and al. 2003. Ecology 84:2347-2363 called "bootstrapped eigenvector". It was asked for that in this forum in January 2005 by J?r?me Lema?tre: "1) Resample 1000 times with replacement entire

Hello: I am working with a stratified survey dataset with sampling weights and I want to use multiple imputation to help with missingness. 1. Is there a way to run an ordered logistic regression using both a multiply imputed dataset (i.e. from mice) and adjust for the survey characteristics using the weight variable? The Zelig package is able to do binary logistic regressions for survey

> the next tool reading the IR does not like phis when it's generating VHDL. If you're doing a conversion from LLVM IR to some other non-SSA IR (like the tool's), you can do the phi node removal yourself as you convert. Basically, every predecessor block referenced by a phi node will have an assignment to that variable before branching. There are techniques to make the resultant

On 30.8.2011, at 19.19, Eli Friedman wrote: > reg2mem won't do quite this transformation... not sure exactly what you need. I need to get rid of phis. This code is compiled from C++ and for some functions there are no phis, but multiple call instructions. I am targeting hardware in the end, and the next tool reading the IR does not like phis when it's generating VHDL. My questions may

...+33 6 37 67 21 40 Courriel-1 : Luis.Tito-de-Morais@ird.fr Courriel-2 : Luis.Titodemorais@univ-brest.fr Pages web : Lab. : http://www-iuem.univ-brest.fr/UMR6539/recherche/equipe-5 Pers. : http://ird.academia.edu/LuisTitodeMorais Reshal : http://www.netvibes.com/reshal#Accueil Biblio. : http://www.citeulike.org/user/ltitodem [[alternative HTML version deleted]]

Dear R-Users, Is anyone aware of a significance test which allows demonstrating that one distribution dominates another? Let F(t) and G(t) be two distribution functions, the alternative hypothesis would be something like: F(t) >= G(t), for all t null hypothesis: F(t) < G(t), for some t. Best wishes, Matthias PS. This one would be ok, as well: F(t) > G(t), for all t null

Dear List: I am working to understand some differences between the results of the svymean() function in the survey package and from code I have written myself. The results from svymean() also agree with results I get from SAS proc surveymeans, so, this suggests I am misunderstanding something. I am never comfortable with "I did what the software" does mentality, so I am working to

Hello, I am running polychoric correlations on a dataset composed of 12 ordinal and binary variables (N =384), using the polycor package. One of the association (between 2 dichotomous variables) is very high using the 2-step estimate (0.933 when polychoric run only between the two variables; but 0.801 when polychoric run on the 12 variables). The same correlation run with ML estimate returns a