st: Re: st: Clogit does not converge (Stata returns “not concave” for every iteration) – possible dummy variable problem in a DCE

[Richard Williams <richardwilliams.ndu@gmail.com>]

This sounds like an incredibly complicated simulation. Are you sure
that you did it right? When I can't get models to converge it is
usually because of problems with the data or with the model. I would
run various descriptive statistics on the data. If you are convinced
you are doing things right, try a different random seed for the
simulation.

Sometimes adding the -difficult- option works miracles.

Also, I would use factor variable notation rather than create my own
dummies. Partly because it is easier, but also because it gives you an
additional error check, e.g. you'll know to be suspicious if you get
573 dummy variables when you were expecting 3.

Sent from my iPad

On Mar 21, 2013, at 7:51 PM, James Buchanan <james.buchanan@dph.ox.ac.uk> wrote:

> Totally skimpy. But it's only a simulation, and it probably helps to think of the simulation as 160 choices, rather than 10 patients. Regardless, I've tried running the same model on 200 patients (i.e. 3200 choices) and I get the same problem. I should have made the latter clear in my initial post, apologies.
>
> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Richard Williams
> Sent: 21 March 2013 23:39
> To: statalist@hsphsun2.harvard.edu
> Subject: st: Re: st: Clogit does not converge (Stata returns “not concave” for every iteration) – possible dummy variable problem in a DCE
>
> I've never run a model like this, but isn't ten subjects a little on the skimpy side.?
>
> Sent from my iPad
>
> On Mar 21, 2013, at 5:17 PM, James Buchanan <james.buchanan@dph.ox.ac.uk> wrote:
>
>> I am analysing the results of a simulated discrete choice experiment. I want to make sure my data matrix is set up correctly prior to launching the DCE. I have simulated 10 patients, each of whom makes 16 choices (2 options in each choice). Each choice has 6 attributes, and each attribute has four levels. The first four attributes are continuous variables. If I regress these four attributes against my dependent variable (pref) using clogit everything works fine. The final two attributes are categorical variables. As soon as I add these variables as dummies (either standard (1,0) dummy variables or using effects coding (1,0,-1)) clogit refuses to converge. Each iteration returns a not concave message, and I get no results.
>>
>> The syntax I am using is: clogit Pref ASCa Time Cost Eff Rel Info1
>> Info2 Info3 Who1 Who2 Who3, group(Unique_Q)
>>
>> Pref = choice variable (1 or 0)
>> ASCa = alternative specific constant for option A Time, Cost, Eff, Rel
>> = continuous attributes Info1, Info2, Info3 = categorical variable 1
>> converted to 3 dummy variables (there is an Info0 but this has been
>> dropped to avoid the usual dummy variable problem) Who1, Who2, Who3 =
>> categorical variable 2 converted to 3 dummy variables (Who0 dropped)
>> Unique_Q = a unique id value for each choice
>>
>> If I add iter(20) to the end of the syntax, I see that the standard errors for Info2 and Info3 are undefined (“.”), and Stata warns me that convergence has not been achieved.
>>
>> My design is efficient (d-error of 0.051899), there is perfect level balance, minimal overlap, and there are no dominated alternatives. I am using the current version of Stata (12.1) on Windows 7.
>>
>> Does anybody have any idea why I'm getting this error?
>>
>>
>>
>> James Buchanan
>> NIHR Doctoral Research Fellow
>> Health Economics Research Centre
>>
>> t: 01865 289262 | e: james.buchanan@dph.ox.ac.uk | w:
>> http://www.herc.ox.ac.uk/people/james
>> Department of Public Health | University of Oxford | Old Road Campus |
>> Headington | Oxford | OX3 7LF
>>
>> T: http://twitter.com/HERC_Oxford | F:
>> http://www.facebook.com/healtheconomicsresearchcentre
>>
>>
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