Thank you Svend for the answer.
So I shouldn't worry even if it is as small as 0.02%?
Azi
> Svend Juul <[email protected]> wrote:
>
> Azi wrote:
>
> I am looking at the predictors of standardised mortality
>
> ratio (SMR) for my cohort. I have two datasets:
>
> -the first one contains death; person-years of observation
>
> and different variable which i want to check as predictors
>
> of smr.
>
> -the second dataset contains the rate of mortality
>
> (adjusted for sex and age) for the reference population.
>
>
>
> After stset and stsplit in the first dataset, i merged it
>
> with the second one and calculated the expected number of
>
> death (e) for my cohort. In order to look at the
>
> predictors of smr i used the following syntax:
>
>
>
> xi: poisson _d i.psy i.cob ......., exposure(e) irr.
>
>
>
> I wonder whether the selection of "e" as the exposure is
>
> correct when my dependent variable is smr?
>
>
>
> When i fit different models, pseudo R^2 is very small
>
> (around 0.02) in all of them. This happens even when I
>
> include variables which influence smr. For all models use of
>
> poisgof gives a good results.
>
> ------------------------------------
>
>
>
> From what you tell us, you did it right, provided the second
>
> dataset contains reference mortality rates for each sex and
>
> age group (not "adjusted" for sex and age). Just one phrase:
>
> I wouldn't call smr the dependent variable; it is a measure
>
> of association or contrast (the dependent variable is death).
>
>
>
> Don't worry about the small pseudo R^2. The interpretation
>
> is dubious for dichotomous outcomes; in my general
>
> understanding a high R^2 would mean that we were able, from
>
> the model, to predict when each individual would die - and
>
> we are hardly that clever yet.
>
>
>
> Good luck,
>
> Svend
>
>
>
> ________________________________________________________
>
> Svend Juul
> Institut for Folkesundhed, Afdeling for Epidemiologi
> (Institute of Public Health, Department of Epidemiology)
> Vennelyst Boulevard 6
> DK-8000 Aarhus C, Denmark
> Phone, work: +45 8942 6090
> Phone, home: +45 8693 7796
> Fax: +45 8613 1580
> E-mail: [email protected]
> _________________________________________________________
>
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