RE: st: RE: gpscore for propensity score of 4 observed groups

["Villa Lora, Juan Miguel" <juanmiguelv@iadb.org>]

no, you misunderstood. A control group is what you need. But I would expect a 'clean' control group without any kind of treatment or a 'placebo taker'. If you want to use a control group with certain grade of treatment you won't get a reliable causal inference. I recommend an article found at http://ftp.iza.org/dp4451.pdf "Evaluating Nonexperimental Estimators for Multiple Treatments: Evidence from Experimental Data"
________________________________________
From: owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] On Behalf Of oconnor7@u.washington.edu [oconnor7@u.washington.edu]
Sent: Tuesday, October 12, 2010 6:09 PM
To: statalist@hsphsun2.harvard.edu
Subject: RE: st: RE: gpscore for propensity score of 4 observed groups

Thanks for your help. Yes, actually the groups consist of three levels of TBI severity and a control group of arm injured patients. Sorry for the confusion. I did not think that having a control would affect the propensity score in this situation.

Stephen

On Tue, 12 Oct 2010, Villa Lora, Juan Miguel wrote:

> Stephen,
> I haven't dealt with such case. Anyway, it seems to me that you don't have a control or comparison group without treatment. This situation may confound your evaluation and your results will be invalid.
> Juan
>
> ________________________________________
> From: owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] On Behalf Of oconnor7@u.washington.edu [oconnor7@u.washington.edu]
> Sent: Tuesday, October 12, 2010 5:32 PM
> To: statalist@hsphsun2.harvard.edu
> Subject: Re: st: RE: gpscore for propensity score of 4 observed groups
>
> Hi Juan,
>
> Yes, this is true, the treatment variable is categorical. I was worried that this would be an issue. That said, what command what provide a propensity score for a categorical variable with four levels?
>
> Stephen
>
> On Tue, 12 Oct 2010, Villa Lora, Juan Miguel wrote:
>
>> Hey Stephen!
>> Before answering your question I'd like to understand your treatment variable. You are stressing that you got four different groups, which makes me think that you are dealing with a categorical variable instead of a continuous variable as it's required for gpscore. Remember that Hirano and Imbens (2005) spell out that this treatment variable must be a normal distributed (one of the basic assumptions of the analysis).  Are you sure your treatment variable is continuous?
>> Juan
>> ________________________________________
>> From: owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] On Behalf Of oconnor7@u.washington.edu [oconnor7@u.washington.edu]
>> Sent: Tuesday, October 12, 2010 5:15 PM
>> To: statalist@hsphsun2.harvard.edu
>> Subject: st: gpscore for propensity score of 4 observed groups
>>
>> Hi,
>>
>> I have technical question regarding gpscore.
>>
>> If my treatment variable is type of injury severity, what should I put for "cutpoints", "index", and "nq_gps"? The treatment level has four different levels of injury severity.
>>
>> What I am seeking is to create a propensity score for the likelihood that a person develops a certain type of injury, in this case TBI, based upon a list of covariates.
>>
>> This is the syntax I used for a preliminary analysis:
>>
>> gpscore  age child_gender prev_anxiety prev_depn prev_adhd prev_behavioral prev_other_mh, t(inj_severity) gpscore(mygps) predict(hat_inj_sev) sigma(hat_sd) cutpoints (inj_severity) index(p50) nq_gps(4)
>>
>> Again, I am unsure of cutpoints, index, and nq_qps given that I have four established groups for the treatment variable.
>>
>>
>> Thank you,
>> Stephen
>>
>>
>>
>>
>> Stephen O'Connor
>> Senior Fellow
>> Harborview Injury Prevention & Research Center
>> Department of Psychiatry & Behavioral Sciences
>> University of Washington at Harborview Medical Center
>>
>>
>>
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