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Re: st: Interpretation of regressionmodel of ln-transformed variable


From   "roland andersson" <rolandersson@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Interpretation of regressionmodel of ln-transformed variable
Date   Thu, 6 Nov 2008 18:05:24 +0100

Thank you Peter

I tried that but unfortunately the model did not converge.

Roland

2008/11/6 Lachenbruch, Peter <Peter.Lachenbruch@oregonstate.edu>:
> You need a space between power and -1
> Check the help for glm
>
> Tony
>
> Peter A. Lachenbruch
> Department of Public Health
> Oregon State University
> Corvallis, OR 97330
> Phone: 541-737-3832
> FAX: 541-737-4001
>
>
> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu
> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of roland
> andersson
> Sent: Wednesday, November 05, 2008 10:54 PM
> To: statalist@hsphsun2.harvard.edu
> Subject: Re: st: Interpretation of regressionmodel of ln-transformed
> variable
>
> I tried the model
>
> xi: glm lengthof stay lapscopy i.appdgn2 i.alderk prepermalign
> precardioscleros  preperdiabetes cons, eform link(power-1) nocons
> and get an error message "unrecognized command:  power"
>
> Roland
>
> 2008/11/5 Nick Cox <n.j.cox@durham.ac.uk>:
>> I doubt that anything is wrong with Tony's model except that
>> -eform("exp(b)")- should just be -eform-.
>>
>> Nick
>>
>> roland andersson
>>
>> Peter and Maarten
>>
>> I am sorry Peter. Your model is not accepted by Stata. I tried
>> different alternativ without success.
>>
>> However I tried Maarten GLM model
>>
>> xi: glm studytime i.drug c_age cons, family(gaussian) link(log) nocons
>> eform
>>
>> on my data and got a different result compared to the regress of the
>> lnLOS. Now laparoscopy has shorter LOS. Which method is correct?
>>
>>
>> 2008/11/5 Lachenbruch, Peter <Peter.Lachenbruch@oregonstate.edu>:
>>
>>> The issue seems to be that hospitals have a closure date on stay when
>>> you are doing a study after patients are certain (or almost certain)
>> to
>>> have been discharged (e.g., all records are from admissions at least
> a
>>> year old).
>>>
>>> An alternative model might fit the reciprocal of the mean rather than
>>> the log of the observations (thus obviating problems with 0 days of
>> stay
>>> - e.g. an outpatient visit to the ER)  in this case you could use
>>> generalized linear models to get
>>> xi: glm LOS  lapscopic i.appdgn age agesq cons, eform("exp(b)")
>>> link(power -1) nocons
>>>
>>>
>>> Tony
>>
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