Thank you for responding.
I am truly grateful.
Apologies for omitting evident and pertinent information.
I am using 3.36. I will update to 3.37. I did not notice the newer version.
I realize I needed to be more specific. The attr(, "var") that I am interested
in is displayed with str(result
On Tue, 11 Feb 2020 15:23:14 +
andertech...@protonmail.com wrote:
> The attr(, "var") that I am interested in is displayed with
> str(results) after the results object is declared. First line of the
> subject code looks like:
>
> results <- (if (multicore) parallel::mcapply else lapply)(uniq
On Tue, 11 Feb 2020 02:33:45 +
AndertechLLC--- via R-help wrote:
> When debugging the code I am not following the generation of values
> in the results object attr(*, "var")" after line 57 completes. These
> values are fed into line 74 (rval <- t(sapply(results, unwrap))).
Which version of t
Good day,
I was looking for some help with understanding a particular portion of the
svyby source code.
When debugging the code I am not following the generation of values in the
results object attr(*, "var")" after line 57 completes.
These values are fed into line 74 (rval <- t(sapply(results,
Hi,
I'm trying to use both the survey package and the anesrake package to
perform raking on my sample dataset, to get the proportions to match up
with population data from the census.
I'm trying the following, but the resulting weights are very large:
> svy.unweighted <- svydesign(ids=~1, dat
could you provide a minimal reproducible example? perhaps use ?dput.
in general the survey package matches all other languages
http://journal.r-project.org/archive/2009-2/RJournal_2009-2_Damico.pdf
here's an example of a minimal reproducible example that does match
http://www.ats.ucla.edu/stat
Hi,
I'm new to R and have encountered two issues in coding using the "survey"
package:
(1) Code from *svytable* using "survey" package does not correspond to
Stata estimates from *svy: tab*. I call
svyd.nation <- svydesign(ids = ~1, probs = ~wt_national, strata =
~stratum, data=nats.sub)
I am trying to age standardize using the svystandardize package in R. I
have successfully managed to hit my SUDAAN based targets for estimates by
sex, but not the total. The total is only a little different, but I'd like
some help knowing why it isn't exact. I've included the SUDAAN code that
gener
Hello Thomas,
I use both svymean (with the expanded sample = people), and svyratio
(voting unit level), using the same design:
design <-svydesign(id=~station + unit, fpc=~probstation+probunits,
data=sample, pps="brewer")
I got different results using the same sample:
svyratio (voting unit)
On Fri, Oct 12, 2012 at 6:56 AM, Sebastián Daza
wrote:
> 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
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 vo
I found the problem. My data were not in a data.frame.
Thanks,
Brent
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Hi. I'm using American Housing Survey (AHS) data with replicate weights. I
want subpopulation estimates. When I try to subset the survey design, I get
an error message. I don't get the error message when not using the replicate
weights (using the regular svydesign function).
Any help would be ap
Hi there, haven't heard from anyone and just wondering if anyone had any
insight! Thanks. :)
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_
Hi there,
I'm new to some of these more advanced regression techniques and also new to
R. This looks like a great forum.
I am trying to examine the association with membership in a group and some
different variables, most of which are (approximately) normally distributed.
Would just do an ANOVA
On Tue, Feb 14, 2012 at 11:45 AM, Kieran Healy wrote:
> Hello,
>
> I'm running R 2.14.1 on OS X (x86_64-apple-darwin9.8.0/x86_64 (64-bit)), with
> version 3.28 of Thomas Lumley's survey package. I was using predict() from
> svyglm(). E.g.:
>
> data(api)
> dstrat<-svydesign(id=~1,strata=~stype, w
Hello,
I'm running R 2.14.1 on OS X (x86_64-apple-darwin9.8.0/x86_64 (64-bit)), with
version 3.28 of Thomas Lumley's survey package. I was using predict() from
svyglm(). E.g.:
data(api)
dstrat<-svydesign(id=~1,strata=~stype, weights=~pw, data=apistrat, fpc=~fpc)
out <- svyglm(sch.wide~ell+mobi
On Tue, 18 May 2010, Vinh Nguyen wrote:
Binder's estimating equations are the usual way of applying weights to a Cox
model, so nothing special is done apart from calling coxph(). To quote the
author of the survival package, Terry Therneau, "Other formulae change in
the obvious way, eg, the weigh
On Tue, May 18, 2010 at 8:50 AM, Thomas Lumley wrote:
>
> > I
>>
>> don't believe so since svycoxph() calls coxph() of the survival
>> package and weights are applied once in the estimating equation. If
>> the weights are implemented in the ratio, could you point me to where
>> in the code this
On Mon, 17 May 2010, Vinh Nguyen wrote:
Dear R-help,
Let me know if I should email r-devel instead of this list. This
message is addressed to Professor Lumley or anyone familiar with the
survey package.
Does svycoxph() implement the method outlined in Binder 1992 as
referenced in the help fil
Dear R-help,
Let me know if I should email r-devel instead of this list. This
message is addressed to Professor Lumley or anyone familiar with the
survey package.
Does svycoxph() implement the method outlined in Binder 1992 as
referenced in the help file? That is, are weights incorporated in th
Dear R-help,
Let me know if I should email r-devel instead of this list. This
message is addressed to Professor Lumley or anyone familiar with the
survey package.
Does svycoxph() implement the method outlined in Binder 1992 as
referenced in the help file? That is, are weights incorporated in th
On Thu, 18 Feb 2010, Richard Valliant wrote:
Should the svyby function be able to work with svyquantile? I get the
error below ...
It works, but you need to either specify ci=TRUE or keep.var=FALSE. The
problem is that svyquantile() by default does not produce standard errors.
svyby(~api0
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.
On Fri, 3 Apr 2009, Paul Jones wrote:
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
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
varia
Hello
I have a problem using the package survey:
I'm trying to calculate the prevalence of a disease in animals sampled using a
2 stages sampling system:
first level: farm randomly chosen within 551 farms
second level: animals randomly chosen in the farms
My data base has this aspect:
On Tue, 12 Feb 2008, Peter Holck wrote:
> Using the survey package I find it is convenient and easy to get estimated
> proportions using svymean, and their corresponding estimated standard
> errors. But is there any elegant/simple way to calculate corresponding
> confidence intervals for those pr
Using the survey package I find it is convenient and easy to get estimated
proportions using svymean, and their corresponding estimated standard
errors. But is there any elegant/simple way to calculate corresponding
confidence intervals for those proportions? Of course +/- 1.96 s.e. is a
reasonab
Good afternoon!
1 I have a bit of a problem with the Survey package, but one that is more
theoretical than practical. If for example on wishes to use some additional
information which comprises of 4 variables with 7, 5,5 and 5 categories
(resulting in 875 post-strata if the whole crossin
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