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RE: Re: st: Linear Trend Tests of ORs


From   Rho YH <mania1@korea.ac.kr>
To   statalist@hsphsun2.harvard.edu
Subject   RE: Re: st: Linear Trend Tests of ORs
Date   Tue, 23 May 2006 09:43:23 +0900 (KST)

Hmm.. It looks like the aformentioned Cochrane-Armitage Test, however I'll check it out.
Thanks.
> ---- Original Message ----
> From : Suzy [scott_788@wowway.com]
> To : statalist@hsphsun2.harvard.edu
> Date : 2006 5 22() 21:24:22
> Subject : Re: st: Linear Trend Tests of ORs
>
>
>Perhaps Szklo and Nieto's book can help: Epidemiology. Beyond the
>Basics, discusses test for trend (dose reponse) in Appendix B (pp 459-462).
>
>Formula is from Mantel:
>
>Mantel N. Chi square tests with one degree of freedom: etensions of the
>Manetel-Haenszel procedure. J Am Stat Assoc. 1963;58: 690-700.
>
>Hope this helps.
>Suzy
>
>Young Hee Rho wrote:
>
>>I have encountered many "trend tests" of linearity concerning odds ratios (OR) of a
>>categorical variable.
>>For example, I am modeling a logistic model Y=b1x1 + b2x2 + b3x3 +b4. x2 is a 5-level
>>categorical variable, for example the level of drinking (while Y is the presence/absence of
>>hyperuricemia). When the results are displayed, the ORs of the 5 levels are shown and
>>the linear trend is shown as a single p value. The individual ORs may not have significance,
>>however the overall trend does. It is said that it was tested through regressing the median of
>>the levels on the ORs. Otherwise in other cases, there are many trend tests of linearity
>>expresed in many papers, however, the actual method is not explained in detail. (It does not
>>apear to come from polynomial contrasts of ANOVA nor from categorical trend tests
>>(Cochrane-Armitage) since the arformentioned test is from values coming from
>>one categorical variable having several estimates. How is this done and how much methods
>>exsist on this topic? Are there any useful references?
>>** For those who got twice this article, I sent this article again since it did not seem to register on
>>Statalist. Many apologies if there was a duplicate delivery.
>>
>
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