I have just found out that the tabodds command may meet what I wanted - linear trend of ORs,
however making multivariate adjustments is not easy (I tried and it gave no results after adjusting
for >2 or 3 variables.) Is there any "immediate command" by just inputing the OR (and CI, if needed)
and the independent variable category and produces a p value?
> ---- Original Message ----
> From : Rho YH [[email protected]]
> To : [email protected]
> Date : 2006�� 5�� 23��(ȭ) 09:43:23
> Subject : RE: Re: st: Linear Trend Tests of ORs
>
>
>Hmm.. It looks like the aformentioned Cochrane-Armitage Test, however I'll check it out.
>Thanks.
>> ---- Original Message ----
>> From : Suzy [[email protected]]
>> To : [email protected]
>> 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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