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Re: st: Proper standard error for a difference in rates for a Poisson distributed count?


From   Stas Kolenikov <skolenik@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Proper standard error for a difference in rates for a Poisson distributed count?
Date   Mon, 18 Oct 2004 14:02:35 -0400

Obviously, there is a lot I don't know about the standards of how
Poisson regressions are fitted and reported, but why not try something
like

xi: poisson rate i.score [aw=expos]

or something of that kind? After fitting the regression, you would
have variables _Iscore_2, _Iscore_3 that would show the difference
from the base category 1 (you can tweak the base category around, see
-help xi-), and the approrpiate tests for the differences from that
base category will be the test statstics reported in the output, and
between the estimated categories, through

test _Iscore_2 - _Iscore_3

see if this helps

Stas

On Mon, 18 Oct 2004 11:55:20 -0400, David Harless <dwharles@vcu.edu> wrote:
> Dear Statalisters:
> I am writing to ask for advice on how to calculate (whether there exists?) a
> proper standard error for a mean *difference* in rates from a Poisson
> distributed count.  Suggestions or citations would be greatly appreciated.
> 
> Here are the details:
> I have counts of the number of failures by groups over time.  In each period,
> there is also a score (from 3 to 5) which is claimed as an (ordinal) rating of
> safety of the group in the time period. Example:
> 
> . list group period score expos failures in 17/23, sepby(group) noobs
>    +----------------------------------------------+
>    | group   period   score      expos   failures |
>    |----------------------------------------------|
>    |     7        1       4    10.0092         17 |
>    |     7        2       5    15.3863         11 |
>    |----------------------------------------------|
>    |     8        1       5   143.2803         93 |
>    |     8        2       4    32.9646         24 |
>    |     8        3       3    31.2676         21 |
>    |     8        4       4    89.2825         63 |
>    |     8        5       3    26.6402          6 |
>    +----------------------------------------------+
> 
> My main analysis is poisson regression with fixed effects for the groups
> (xtpoisson, fe) that would include dummy variables for the scores.  But I would
> also like to provide a descriptive table that illustrated the change in failure
> rate as the score changed -- and have that table include a correct standard error.
> 
> My problem would be straightforward if I simply wanted to present mean failure
> rates by score:
> . gen rate=failures/expos
> . table score [aweight=expos] , c(m rate) format(%9.3f)
> ----------------------
>   mean(rate)
> ----------+-----------
>          3 |      0.964
>          4 |      0.847
>          5 |      0.875
> ----------------------
> 
> And the proper standard errors may be obtained using -ci- :
> 
> . sort score
> . by score: ci failures, exposure(expos) poisson
> -> score = 3
>                                                           -- Poisson  Exact --
>      Variable |   Exposure        Mean    Std. Err.       [95% Conf. Interval]
> -------------+---------------------------------------------------------------
>      failures |       4684    .9637415    .0143443          .93583    .9922742
> 
> And so on.
> 
> But I want my table to show the means of the *differences* in failure rates (by
> group) for different scores.  Along the lines of:
> 
> . tsset group period
>         panel variable:  group, 1 to 153
>          time variable:  period, 1 to 7
> 
> . gen d_rate=d.rate
> (153 missing values generated)
> 
> . gen l_score=l.score
> (153 missing values generated)
> 
> . gen sum_expos=expos+l.expos
> (153 missing values generated)
> 
> . table l_score score [aweight=sum_expos], c(m d_rate ) f(%9.3f)
> ----------------------------------
>    l_score |      3       4       5
> ----------+-----------------------
>          3 | -0.029  -0.069  -0.074
>          4 | -0.026  -0.009  -0.038
>          5 |          0.135  -0.025
> ----------------------------------
> 
> I've already made an assumption in weighting by the sum of exposures over the
> two periods in which the difference in rates are calculated.  Perhaps there is a
> better way to incorporate this information, but the mean of differences in rates
> must be calculated in a way that reflects different exposures.
> 
> So my question is:  Can one calculate a proper standard error for a difference
> in rates for a Poisson distributed count, as in the above example?


-- 
Stas Kolenikov
http://stas.kolenikov.name
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