Displaying 20 results from an estimated 3000 matches similar to: "Survey Package with Binary Data (no Standard Errors reported)"
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 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 =
2005 Jun 16
1
Survey - Cluster Sampling
Dear WizaRds,
I am struggling to compute correctly a cluster sampling design. I want
to do one stage clustering with different parametric changes:
Let M be the total number of clusters in the population, and m the
number sampled. Let N be the total of elements in the population and n
the number sampled. y are the values sampled. This is my example data:
clus1 <-
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
2007 Dec 19
2
4 questions regarding hypothesis testing, survey package, ts on samples, plotting
Good morning!
I have 4 questions which trouble me:
1. I want to test the hypothesis that the 2 proportions (the mean of a binomial) which come from 2 different samples are equal. I want to use the following function
z= (p1-p2)/ sqrt((p1(1-p1)/n1)+(p2(1-p2)/n2)) which is one of the standard formulas for this case. Is there such a function in R?
p1=the proportion from the first sample
n1=the
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
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
2008 Aug 15
2
Design-consistent variance estimate
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
2012 Oct 11
2
survey package question
Hello,
I have got a cluster sample using an election dataset where I already
had the final results of a county-specific election. I am trying to
figure out what would be the best sampling design for my data.
The structure of the dataset is:
1) polling station (in general schools where people vote, for a
county, for example, there are 15 polling stations)
2) inside each polling station, there
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
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
2008 Aug 26
2
svymeans question
I have the following code which produces the output below it
clus1 <- svydesign(ids = ~schid, data = lower_dat)
items <- as.formula(paste(" ~ ", paste(lset, collapse= "+")))
rr1 <- svymean(items, clus1, deff='replace', na.rm=TRUE)
> rr1
mean SE DEff
W525209 0.719748 0.015606 2.4932
W525223 0.508228 0.027570 6.2802
W525035 0.827202
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
...
2006 Jul 07
2
Multistage Sampling
Dear WizaRds, dear Thomas,
First of all, I want to tell you how grateful I am for all your
support. I wish I will be able to help others along one day the same way
you do. Thank you so much. I am struggling with a multistage sampling
design:
library(survey)
multi3 <- data.frame(cluster=c(1,1,1,1 ,2,2,2, 3,3), id=c(1,2,3,4,
1,2,3, 1,2),
nl=c(4,4,4,4, 3,3,3, 2,2), Nl=c(100,100,100,100,
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
2006 Jun 18
1
Post Stratification
Dear WizaRds,
having met some of you in person in Vienna, I think even more fondly
of this community and hope to continue on this route. It was great
talking with you and learning from you. Thank you. I am trying to work
through an artificial example in post stratification. This is my dataset:
library(survey)
age <- data.frame(id=1:8, stratum=rep(
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
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
2008 Sep 09
1
survey package
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,
2008 Sep 09
1
survey package
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,