I have individual data with multiple records per patient after I have
split the follow up time depending on year and age and have merged a
variable for the incidence rate per 100.000 personyears. With the
command
xi:strate i.timeperiod,smr(inc) per (100000)
I get the following result
+-----------------------------------------------------------+
timeperiod D E SMR Lower Upper
-----------------------------------------------------------
1 7 0.43 16.102 7.677 33.777
2 5 1.65 3.032 1.262 7.284
3 14 2.11 6.642 3.934 11.215
+-----------------------------------------------------------+
I want to test for the linear trend over the timeperiods.
If I try the smrby on this result I get:
. smrby D E, by(timeperiod) trend
Observed Expected -- Poisson Exact --
timeperiod D E O/E (%) [95% Conf. Interval]
1 7 0.4300 1627.9*** 655 3354
2 5 1.6500 303.0 98 707
3 14 2.1100 663.5*** 363 1113
may not use noninteger frequency weights
r(401);
Why do I get this error message?
According to your second choice I use the following model on this result.
glm D timeperiod, family(poisson) lnoffset(E) eform
Iteration 0: log likelihood = -9.6767233
Iteration 1: log likelihood = -9.5071336
Iteration 2: log likelihood = -9.5068971
Iteration 3: log likelihood = -9.5068971
Generalized linear models No. of obs = 3
Optimization : ML Residual df = 1
Scale parameter = 1
Deviance = 7.236772128 (1/df) Deviance = 7.236772
Pearson = 6.884656839 (1/df) Pearson = 6.884657
Variance function: V(u) = u [Poisson]
Link function : g(u) = ln(u) [Log]
AIC = 7.671265
Log likelihood = -9.506897131 BIC = 6.13816
OIM
D IRR Std. Err. z P>z [95% Conf. Interval]
timeperiod .7561818 .2108008 -1.00 0.316 .4378616 1.305917
E (exposure)
ie there is no linear trend p=0.316
Is this a correct use of the glm model? Or can I use some other method
on the original dataset? If I collapse the dataset what happens with
the incidensvariable which should not be aggregated but stay the same.
Or do I have to collapse the dataset and merge the incidensvariable
after the collapse?
Roland Andersson
2007/10/18, raoul reulen <[email protected]>:
> Hi
>
> I'm not exactly sure what you want to do, but the title of the message
> suggests you want to do a test for linear trend accros several SIRs.
> What I normally do is use smrby.ado because it includes a test for
> trend and heterogeneity. Alternatively, you might want to model the
> SIRs by using a GLM model with a Poisson error structure and then fit
> the factor of interest as a consecutive non-negative integer variable.
> Make sure you collapse your data before you model it.
>
> .collapse (sum) _d E pyrs, by(timeperiod)
> .xi, noomit:glm _d i.timeperiod if E!=0,fam(pois) lnoffset(E) eform noconstant
>
> gives you the SIRs
>
> .xi, noomit:glm _d timeperiod if E!=0,fam(pois) lnoffset(E) eform noconstant
>
> gives you the p-value for linear trend
>
> _d is the numner of events, E the number of expected. The p-value for
> timeperiod should give you the test for linear trend accross the
> groups.
>
>
> Hope it helps
>
> Raoul Reulen
> Cancer Research UK Graduate Training Fellow
>
>
>
>
>
> On 17/10/2007, roland andersson <[email protected]> wrote:
> > I have used strate.ado to calculate standardised incidence ratios with
> > standardisation for age, sex and timepriod. I want to make inferences
> > on the development of the SIRs over three timeperiods. Can you help me
> > with instruction how to do this?
> > *
> > * For searches and help try:
> > * http://www.stata.com/support/faqs/res/findit.html
> > * http://www.stata.com/support/statalist/faq
> > * http://www.ats.ucla.edu/stat/stata/
> >
>
>
> --
> -------------------------------------------------------
> Raoul C. Reulen
> Cancer Research UK Training Fellow
> *
> * For searches and help try:
> * http://www.stata.com/support/faqs/res/findit.html
> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
>
*
* For searches and help try:
* http://www.stata.com/support/faqs/res/findit.html
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
