You might want to look at the various wtd.* functions in the Hmisc
package:
require(Hmisc)
?wtd.stats
'wtd.mean' is just one of the functions supplied. You might want to
contemplate the simplicity of Harrell's function code, since it is not
hidden. Just type:
wtd.mean
--
David.
On Mar 3, 2012, at 2:04 PM, Hed Bar-Nissan wrote:
Following David example if i just wanted to do means
would multiplying the cases according to the weight do the work?
Something like this on a data.frame
(Must be a simpler way to do it with R - the sapply scope confused me)
weightBy <- function(origDataFrame,weightVector)
{
case_Number_After_Weighting = sum(weightVector);
#print ( "case_Number_After_Weighting =
");#print(case_Number_After_Weighting );
data.weighted.local = data.frame
( 1:case_Number_After_Weighting );
assign("data.weighted.tmp",data.weighted.local,env=globalenv())
sapply(1:NCOL(origDataFrame),
function(colNo) {
#print ( "dealing with colomn ");#print(colNo);
data.weighted.tmp[,colNo] =
unlist(
sapply(1:NROW(origDataFrame),
function(x) rep(origDataFrame[x,colNo],
times=weightVector[x] )
)
)
names(data.weighted.tmp)[colNo] <- names(origDataFrame)
[colNo]
assign("data.weighted.tmp",data.weighted.tmp,env=globalenv())
#print (data.weighted.tmp);
}
)
data.weighted.local = data.weighted.tmp;
rm(data.weighted.tmp, envir=globalenv());
return(data.weighted.local);
}
data.recieved <- data.frame(
f1 = factor(c(2,1,1,1), labels = c("Yes", "No")),
f2 = factor(c(1,2,3,4), labels = c("One", "Two","Three","Four"))
);
weight=c(10, 1, 1, 1)
weightBy(data.recieved,weight);
On Fri, Feb 24, 2012 at 8:03 AM, Thomas Lumley <tlum...@uw.edu> wrote:
>On Fri, Feb 24, 2012 at 9:40 AM, David Winsemius <dwinsem...@comcast.net
> wrote:
>
> On Feb 23, 2012, at 3:27 PM, Hed Bar-Nissan wrote:
>
>> It's really weighting - it's just that my simplified example was
too
>> simplified
>> Here is my real weight vector:
>> > sc$W_FSCHWT
>> [1] 14.8579 61.9528 3.0420 2.9929 5.1239 14.7507 2.7535
>> 2.2693 3.6658 8.6179 2.5926 2.5390 1.7354 2.9767
9.0477
>> 2.6589 3.4040 3.0519
>> ....
>
>
> You should always convey the necessary complexity of the problem.
>
>>
>>
>> And still it should somehow set the case weight.
>> I could multiply all by 10000 and use maybe your method but it
would
>> create such a bloated dataframe
>>
>> working with numeric only i could probably create weighted means
>>
>> But something simple as WEIGHTED BY would be nice.
>
>
> The survey package by Thomas Lumley provides for a wide variety of
weighted
> analyses.
Yes. It doesn't do everything that SPSS WEIGHTED BY will do, but it
does a lot. SPSS is more general partly because it cheats -- it
doesn't always compute the right standard errors if the weights are
sampling weights [SPSS now has some proper survey analysis commands,
which do get the right standard errors, but are more limited]
- thomas
--
Thomas Lumley
Professor of Biostatistics
University of Auckland
David Winsemius, MD
West Hartford, CT
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