similar to: 3-Way Crosstab using survey package

Displaying 20 results from an estimated 5000 matches similar to: "3-Way Crosstab using survey package"

2010 Mar 26
1
return.replicates in survey pkg
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
2012 Aug 10
1
Direct Method Age-Adjustment to Complex Survey Data
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
2010 Aug 25
1
Surprising behaviour survey-package with missing values
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
2010 Jun 03
1
problem with 'svyby' function from SURVEY package
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
2011 Mar 07
1
Risk differences with 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
2012 Apr 13
2
problem with svyby and NAs (survey package)
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 ...
2012 Oct 02
2
svyby and make.formula
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
2010 Feb 18
1
survey package question
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
2006 Apr 22
1
svyby example returns error
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
2017 Jul 09
2
Help with ftable.svyby
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
2017 Jul 09
0
Help with ftable.svyby
try resetting your factor levels and re-run? q50 <- update( q50 , INCOME = factor( INCOME ) , AGECL = factor( AGECL ) , RACECL = factor( RACECL ) ) On Sun, Jul 9, 2017 at 2:59 PM, Orsola Costantini via R-help < r-help at r-project.org> wrote: > Hi all, > > When I try the following with pkg Survey it returns the error below: > > ftable(svyby(~INCOME, ~AGECL+RACECL,
2010 Aug 18
1
svyquantile w/ svyby is returning an 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
2011 Aug 18
1
Comparison of means in survey package
Dear list colleagues, I'm trying to come up with a test question for undergraduates to illustrate comparison of means from a complex survey design. The data for the example looks roughly like this: mytest<-data.frame(harper=rnorm(500, mean=60, sd=1), party=sample(c("BQ", "NDP", "Conservative", "Liberal", "None", NA), size=500,
2009 Mar 11
1
CI from svyquantile in survey package
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,
2012 Sep 21
1
Exactly Replicating Stata's Survey Data Confidence Intervals in R
Hi everyone, apologies if the answer to this is in an obvious place. I've been searching for about a day and haven't found anything.. I'm trying to replicate Stata's confidence intervals in R with the survey package, and the numbers are very very close but not exact. My ultimate goal is to replicate Berkeley's SDA website with R (http://sda.berkeley.edu/), which seems to
2005 May 26
1
Survey and Stratification
Dear WizaRds, Working through sampling theory, I tried to comprehend the concept of stratification and apply it with Survey to a small example. My question is more of theoretic nature, so I apologize if this does not fully fit this board's intention, but I have come to a complete stop in my efforts and need an expert to help me along. Please help: age<-matrix(c(rep(1,5), rep(2,3),
2003 Sep 20
4
using aggregate with survey-design and survey functions
Hi R users, I am trying to use the aggregate function with a survey design object and survey functions, but get the following error. I think I am incorrectly using the syntax somehow, and it may not be possible to access variables directly by name in a survey-design object. Am I right? How do I fix this problem? I have used aggregate with "mean" and "weighted.mean", and
2003 Feb 12
2
Various Errors using Survey Package
Hi, I have been experimenting with the new Survey package. Specifically, I was trying to use some of the functions on the public-use survey data from NHIS (2000 Sample Adult file). Error 1): The first error I get is when I try to specify the complex survey design. nhis.design<-svydesign(ids=~psu, probs=~probs, strata=~strata, data=nhis.df, check.strata=TRUE) Error in svydesign(ids =
2009 Apr 03
1
Survey Package with Binary Data (no Standard Errors reported)
Hi, I'm trying to get standard errors for some of the variables in my data frame. One of the questions on my survey is whether faculty coordinate across curriculum to include Arts Education as subject matter. All the responses are coded in zeros and ones obviously. For some of the other variables I have a 2 for those that responded with "Don't Know". I'm getting NA for
2006 Dec 30
1
Crosstab from sql dump
Hello all,, Im looking for a simple function to produce a crosstab from a dumped sql query result. Its very hard to produce crosstabs with most databases (Access being the exception), so with the vast array of R packages, Im sure this has to have already been implemented somewhere. Examples are always good: Take a csv dump like name code user1 100 user2 100 user1 200 user2 210 user1 300 user2