Guys,
This is trivial, but I just tried installing Clarify from the archive version, and found the archive was missing the stata.toc and clarify.pkg files. Stata seems to want these files to install. I went ahead and took the files from the Clarify web site so I'm all set; I thought I would mention it to help the next guy.
Best,
Kevin
Kevin Esterling
Asst. Professor
Department of Political Science
University of California, Riverside
900 University Ave.
Riverside, CA 92521
http://socrates.berkeley.edu/~kest
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Hello,
I'm using Amelia to impute data and Clarify to run regressions on the
five imputed datasets produced by Amelia. Clarify does not produce
the stats. for model fit (I'm particularly interested in R2, Adj. R2,
and F). Up to this point, I've been using Stata's regular regression
command (outside of Clarify) to generate the same regression on all
five imputed datasets to get these values, which I then average over
the five sets of results to get the overall figures for the MI
results. But if there are lots of regressions, this is pretty time
consuming.
Has anyone out there written any code to automate this procedure in
Stata? (I don't have a lot of programming experience.) If so, would
you be willing to share it?
Thanks,
Strom
--
Strom C. Thacker
Susan Louise Dyer Peace Fellow
Hoover Institution
Stanford University
Stanford, CA 94305-6010
650-725-3432
650-723-1687 (fax)
sthacker(a)bu.edu
http://www.bu.edu/sthacker
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Hello,
I'm using Amelia to impute data and Clarify to run regressions on the
five imputed datasets produced by Amelia. Clarify does not produce
the stats. for model fit (I'm particularly interested in R2, Adj. R2,
and F). Up to this point, I've been using Stata's regular regression
command (outside of Clarify) to generate the same regression on all
five imputed datasets to get these values, which I then average over
the five sets of results to get the overall figures for the MI
results. But if there are lots of regressions, this is pretty time
consuming.
Has anyone out there written any code to automate this procedure in
Stata? (I don't have a lot of programming experience.) If so, would
you be willing to share it?
Thanks,
Strom
--
Strom C. Thacker
Susan Louise Dyer Peace Fellow
Hoover Institution
Stanford University
Stanford, CA 94305-6010
650-725-3432
650-723-1687 (fax)
sthacker(a)bu.edu
http://www.bu.edu/sthacker
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Thanks Bill & Lanny. I'm forwarding this to the Clarify and Relogit
mailing lists so others might see too. Gary
: Gary King, King(a)Harvard.Edu http://GKing.Harvard.Edu :
: Center for Basic Research Direct (617) 495-2027 :
: in the Social Sciences Assistant (617) 495-9271 :
: 34 Kirkland Street, Rm. 2 HU-MIT DC (617) 495-4734 :
: Harvard U, Cambridge, MA 02138 eFax (928) 832-7022 :
On Thu, 15 May 2003, William Berry wrote:
> Folks,
>
> As I noted in my previous email, Clarify and Relogit are designed to
> simulate quantities of interest for case n from the estimation sample with
> the command "setx [n]." As the exchange that follows shows, my colleague,
> Lanny Martin, has devised a clever strategy for using Clarify and Relogit
> to simulate quantities of interest for out-of-sample cases. Using Clarify
> as an example, one appends the out of sample cases to the estimation data
> set (adding a dummy variable which indicates whether a case is in the
> estimation sample (insample=1) or out of sample (insample=0). Then one
> uses the command
>
> estsimp modelname depvar indepvars if insample==1
>
> to estimate one's model using just the cases for which insample equals
> 1. Then one uses the command
>
> setx[#]
>
> where # is the observation number for a case for which insample equals 0.
>
> Perhaps you might consider noting this strategy in the next version of your
> documentation for Clarify and Relogit. (While the "if" qualifier is
> included in your description of the estsimp and relogit commands, its
> usefulness for out-of-sample predictions is not immediately obvious.)
>
> This strategy also creates the option for users to input independent
> variable values for a set of hypothetical cases by specifying values in an
> input file. While for most applications, using setx commands to assign
> independent variable values is simpler than inputting these values from a
> file (through, for example, the command "setx mean"), there are other cases
> where it would be simpler to use an input file... in which one can enter
> just variable values in a spreadsheet and avoid the need to type many
> commands with long lists of variable names.
>
> Bill
>
> >X-Sender: lanny@letter.net@mail.letter.net
> >X-Mailer: QUALCOMM Windows Eudora Version 5.2.0.9
> >Date: Thu, 15 May 2003 09:54:28 -0400
> >To: William Berry <wberry(a)garnet.acns.fsu.edu>
> >From: "Lanny W. Martin" <lmartin(a)garnet.acns.fsu.edu>
> >Subject: Re: clarify
> >X-Note: Report abuse to abuse(a)emailsrvr.com
> >X-From: lmartin(a)garnet.acns.fsu.edu - user139.net031.fl.sprint-hsd.net
> >([207.30.5.139]), outgoing 1.
> >X-Note: HELOBOGUS, IPMX (-1)
> >
> >
> >Bill,
> >
> >I just did a little experiment to see whether my suggestion yesterday
> >would work, and the good news is that I think it does. I took two
> >separate datasets that had the same explanatory variables (actually, I
> >just created the two separate data sets by splitting my original data set
> >into two files). Then, within each dataset I created a variable "sample"
> >which took a value of 1 for all obs. in one dataset and 0 for all obs. in
> >the other dataset. I then just appended one data set to the other.
> >
> >Next, using clarify, I ran:
> >
> >estsimp modelname variables if sample==1,
> >
> >which generated simulated parameters based on only my sample observations
> >(i.e., the observations in the first of the two datasets that were
> >appended). Then I just setx as usual with:
> >
> >setx [#],
> >
> >but the # I used was an observation that was NOT in the estimation sample
> >(i.e., from the second of the two datasets that were appended).
> >
> >I checked everything to make sure that setx was using the correct
> >observation, and it was. I also downloaded relogit (since I should
> >probably have it anyway) and tried the same thing, and it works fine.
> >
> >So, solving the problem basically just boils down to appending the
> >out-of-sample data to the sample data, doing relogit with an IF condition,
> >and then doing setx to an out-of-sample observation. A little more
> >brute-force than changing code, but it looks like everything worked correctly.
> >
> >Lanny
> >
> >
> >At 05:09 PM 5/14/2003 -0400, you wrote:
> >>Hi Lanny...
> >>
> >>The short answer is yes; you have it right. But just to be precise...
> >>
> >>It's actually RELOGIT that I'd be using to estimate the model. But
> >>RELOGIT relies on the setx command in Clarify to specify a set of X
> >>values for which predicted Pr(Y=1) is to be calculated. With the
> >>existing setx command, one can set the values of the Xs to the X values
> >>for observation number n in the estimation data set with the command
> >>"setx [n]." I would be looking to modify the code (I presume in the
> >>'setx.ado' file) so that the command "setx [n]" would set X values to the
> >>X values of the nth case in a user-specified (non-estimation) data set...
> >>or I suppose, leave setx alone but create another command, say "setnewx
> >>[n]", that would do the same thing.
> >>
> >>Thanks for your willingness to take a quick look and see if what I want
> >>to do might be doable in a "quick easy fix" to the Clarify code.
> >>
> >>Bill
> >>
> >>At 03:36 PM 5/14/2003 -0400, you wrote:
> >>
> >>>Hey Bill,
> >>>
> >>>I was going to sit down with clarify for a few minutes, but I wanted to
> >>>make sure I understood your question first: So, what you want to do is
> >>>estimate your model as usual in clarify using "estsimp" on one sample of
> >>>data, then you want to set the x values equal to the values of the
> >>>explanatory variables for observations that are outside your
> >>>dataset. And after you do this, you would just generate whatever
> >>>quantities of interest to you. Is that right?
> >>>
> >>>Lanny
> >>>
> >>>___________________________________
> >>>Lanny W. Martin
> >>>Assistant Professor
> >>>Department of Political Science
> >>>Florida State University
> >>>Tallahassee, FL 32306-2230
> >>>
> >>>Email: lanny.martin(a)fsu.edu
> >>>Web: http://garnet.acns.fsu.edu/~lmartin/
> >>>
> >>>Phone: (850) 644-7328
> >>>Fax: (850) 644-1367
> >>>___________________________________
> >>
> >>
> >>****************************************************
> >>William D. Berry
> >>Marian D. Irish Professor of Political Science
> >>Department of Political Science
> >>Florida State University
> >>Tallahassee, FL 32306-2230
> >>e-mail: wberry(a)garnet.acns.fsu.edu
> >>voice: 850-644-7321 FAX: 850-644-1367
> >>http://garnet.acns.fsu.edu/~wberry
> >>****************************************************
>
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