similar to: Comparison of means in survey package

I'm trying to use the survey package to calculate a risk difference with confidence interval for binge drinking between sexes. Variables are X_RFBING2 (Yes, No) and SEX. Both are factors. I can get the group prevalences easily enough with result <- svyby(~X_RFBING2, ~SEX, la04.svy, svymean, na.rm = TRUE) and then extract components from the svyby object with SE() and coef() to do the

Hello all, This is something that I am sure has a really suave solution in R, but I can't quite figure out the best (or even a basic) way to do it. I have a simple linear regression that is fit with lm for which I would like to estimate the x intercept with some measure of error around it (confidence interval). In biology, there is the concept of a developmental zero - a temperature under

hello, can someone tell me how to generate the means for a data frame that looks like this? My data frame has many more variables, but I won't bother you with those; these are the one's that I'm interested in. Needless to say, z is the variable in which I'm interested. I'd like to find out the mean score of z for NDP managers, Conservative managers and Liberal managers

Hi, I'm trying to compute survey svytable statistic on subsets by using the svyby function. Here is the code: b<-svyby(~V024+V751, by=~V025, design=strat2, svytable, round=TRUE) The vars, V024, V751 and V025 are factors. The by var has 2 levels, and hence there will be two subsets. strat2 is created by the svydesign function. It's giving me the following error: >

svymean w/ svyby is working for me... > svyby(~visitcnt, ~agegrp3.f, svymean, design=svydes) agegrp3.f visitcnt se.visitcnt 18-44 18-44 8.755552 0.4953235 45-64 45-64 10.131555 0.5347806 65+ 65+ 9.588802 0.4323629 svyquantile is working for me... > svyquantile(~visitcnt, quantiles=c(.25, .5, .75), ties="rounded", design=svydes) 0.25

Hello I'm trying to get the proportion "true" for dichotomous variable for various subgroups in a survey. This works fine, but obviously doesn't give proportions directly: svytable(~SurvYear+problem.vandal, seh.dsn, round=TRUE) problem.vandal SurvYear FALSE TRUE 1995 8906 786 1997 17164 2494 1998 17890 1921 1999 18322 1669 2001 17623 2122 ...

A stupid question but does anyone know how to express the actual colours used by the main Canadian political parties? I want to do a couple of ggplot2 plots and have lines or rectangles that accurately reflect the party colours. I can probably play around with RColorBrewer or something to figure it out but if some some already has got them it would save me some time especially with the NDP

Hello, Although my R code for the svymean () and svyquantile () functions works fine, I am stuck with the svyby () and make.formula () functions. I got the following error messages. - Error: object of type 'closure' is not subsettable # svyby () - Error in xx[[1]] : subscript out of bounds # make.formula () A reproducible example is appended below. I would appreciate if

Hi, I’m using the svyby for total statistics, for example: svyby(~p_igov,~div_a,desenho_nps,svytotal,drop.empty.groups=TRUE,vartype =c("se","var","cvpct")) In the numerical variable p_igov (and others) I have many non responses but if I maintain the NA it doesn’t work. summary(base_nps$p_igov) Min. 1st Qu. Median Mean 3rd Qu. Max. NA's

Hello, I'm using a complex survey dataset and my goal is to simply spit out a bunch of probability-weighted outcome variable means for the different levels of covariate. So I first define the structure of the study design (I'm using the CDC's NHANES data): dhanes <- svydesign(id=~PSU, strat=~STRATA, weight=~lab_weight, data=final, nest=TRUE) No problem there. Now I use the

Hello dear R users! I did not find a function which gives information about the number of digits of a value shown by R. Do you know one? I need it to solve the problem (see RFAQ 7.31)that 0.2==0.2+0.1-0.1 FALSE The solution suggested in RFAQ is to use isTRUE(all.equal(0.2,0.2+0.1-0.1)) But if I want to compare inequality: 0.2<=0.2 +0.1-0.1 TRUE but 0.2<=0.2 +0.1-0.1 FALSE bad! but in

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

Should the svyby function be able to work with svyquantile? I get the error below ... data(api) dclus1<-svydesign(id=~dnum, weights=~pw, data=apiclus1, fpc=~fpc) svyby(~api00, design=dclus1, by = ~stype, quantiles=c(.25,.5,.75), FUN=svyquantile, na.rm=T ) > Error in object$coefficients : $ operator is invalid for atomic vectors A

Estimados usuarios: Estoy intentando reproducir el ejemplo 6.4 de Thomas Lumley. Complex Survey. Editorial Wiley. 2010 (ver la página en google:

I am having trouble understanding (i.e. getting) confidence intervals from the survey package. I am using R version 2.8.1 (2008-12-22) and survey package (3.11-2) on FC7 linux. To simplify my question I use an example from that package: R> data(api) R> dclus1<-svydesign(id=~dnum, weights=~pw, data=apiclus1, fpc=~fpc) R> (tst <- svyby(~api99, ~stype,

Okay in this plea for help I''m going to repeat some of what i posted before but with a larger amount of background info in the hope that i can get a decent grip on ferret before it wriggles away.. Firstly, what does installing the acts_as_ferret plugin actually do? I install it and add it to my model and then the index is automatically generated and a few methods are added to it and

I get error trying to run examples from 'svyby' help page (?svyby in package "Survey"): # code data(api) dclus1<-svydesign(id=~dnum, weights=~pw, data=apiclus1, fpc=~fpc) svyby(~api99, ~stype, dclus1, svymean) # error message > Error in match.arg(vartype, several.ok = TRUE) : unused argument(s) (several.ok ...) Is this a version problem? I'm running R

I have to build an array through both activerecord and also through a ferret index. I was hoping to find a way of sorting the array as i combine the two so def advanced_search(search_text, store, format, sortby) # find items in ferret index items = Item.find_by_contents(search_text) # and now find all the items from a certain store or category items_from_sql = Item.find_by_sql("SELECT *

Dear list, I got some surprising results when using the svytotal routine from the survey package with data containing missing values. Some example code demonstrating the behaviour is included below. I have a stratified sampling design where I want to estimate the total income. In some strata some of the incomes are missing. I want to ignore these missing incomes. I would have expected that

Hi all, When I try the following with pkg Survey it returns the error below: ftable(svyby(~INCOME, ~AGECL+RACECL, svymean, design=q50), rownames=list(AGECL=c("<35", "35-44", "45-54", "55-64", "65-74", ">=75"), RACECL=c("white non hispanic", "non white or