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st: Re: Variable names incompatable with aflogit?


From   "Michael Blasnik" <michael.blasnik@verizon.net>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: Re: Variable names incompatable with aflogit?
Date   Fri, 11 Aug 2006 15:06:39 -0400

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which aflogit

If this ado file is from an early version of Stata it may have an 8
character limit on variable names, which would be violated by the variables
created by xi.  If this is the case, you may be able to get a newer version
of the ado file or you could rename alcohol as alc so that shorter variable
names are created.

M Blasnik

----- Original Message -----
From: "rps" <rps@uakron.edu>
To: <statalist@hsphsun2.harvard.edu>
Sent: Friday, August 11, 2006 2:09 PM
Subject: st: Variable names incompatable with aflogit?


I have encountered the following problem when using the aflogit (sbe21.pkg)
user-supplied module for calculating population attributable fraction (AF)
following a logistic regression (the data set is tuyns.dta, which is
distributed with the package):

The following logistic regression command is issued:

xi: logit case i.alcohol [fw=3Dn]

which produces:

i.alcohol         _Ialcohol_0-3       (naturally coded; _Ialcohol_0 omitted=
)

<snip>

Then the aflogit command is given:

aflogit _Ialcohol* [fw=3Dn], cc

which produces the following error:

Population attributable fraction from logistic regression
Case-control data (n=3D975)

Using weights [fweight =3D n]

Term      Ref.     A.F.        s.e.      [95% Conf. Int.]*
----------------------------------------------------------
l_1 not found
r(111);

Referring to the model terms explicitly does not help, as in

aflogit _Ialcohol_1 _Ialcohol_2 _Ialcohol_3 [fw=3Dn], cc

However, renaming _Ialcohol_1 _Ialcohol_2 _Ialcohol_3 as alcohol1 alcohol2
alcohol3, respectively, allows the aflogit module to execute:
<snip>
Any insight anyone can give as to why aflogit doesn=B9t accept the original
indicator variable names will be appreciated. For the present example,
renaming the variables is a reasonable solution, but it becomes tedious is
there are several factors in the model each with multiple indicator
variables.

Thanks,

Richard Steiner
The University of Akron

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