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RE: st: Test selection for effects of a number of variables on a dependent variable


From   Tim Evans <Tim.Evans@wmciu.nhs.uk>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   RE: st: Test selection for effects of a number of variables on a dependent variable
Date   Wed, 12 Jun 2013 11:58:34 +0100

Nick,

Sound advice!

Best wishes 

Tim


-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Nick Cox
Sent: 12 June 2013 11:55
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: Test selection for effects of a number of variables on a dependent variable

The question of how to handle social isolation (4 different variables) and ethnicity (5 variables) depends on what those 9 variables are how you think they might affect your response.  In principle, -ologit- can handle measured, counted and indicator/dummy predictors with equal ease.


Nick
njcoxstata@gmail.com


On 12 June 2013 11:49, Nick Cox <njcoxstata@gmail.com> wrote:
> Several confusions here.
>
> Quite what you mean by "factor variable" is unclear (I surmise that 
> you may be confusing Stata with R, for example), but, regardless,
> -regress- allows any kind of numeric variable to be the response, even 
> down to the level of a binary variable. How far that is a good idea 
> depends on the circumstances and Stata trusts you to make a sensible 
> decision.
>
> There is no limitation whereby -mlogit- is restricted to 3 outcomes.
> What prompted that? Numerous different outcomes may be difficult or 
> even impossible to model comfortably or at all, but that's a different 
> matter.
>
> What's crucial is exactly what "stage of diagnosis" means. It could, 
> for all I know, a graded or ordinal scale, in which case I would try
> -ologit- first.
>
> I have to recommend _much_ more reading before analysis. These are 
> basic misunderstandings of statistics and indeed Stata. The textbooks 
> of Alan Agresti are excellent choices.
>
> Nick
> njcoxstata@gmail.com
>
>
> On 12 June 2013 11:22, Tim Evans <Tim.Evans@wmciu.nhs.uk> wrote:
>> Hi all,
>>
>> I am using Stata 11.2, and have a cohort of patients diagnosed with a particular type of cancer and have a couple of questions to ask of my data. The first relates to the effects of certain variables (social isolation, deprivation, stage at diagnosis etc) on survival time - this I think I have sorted out. However, one question I have to answer is:
>>  'does ethnicity or social isolation have an effect on stage at diagnosis (controlling for the other factors).'
>>
>> My stage at diagnosis variable has 6 different values, social isolation has 4 different variables and ethnicity has 5 variables. Originally I thought I would be able to model this using -mlogit-, but this appears to me, to only be appropriate when the dependent variable has 3 different values (and mine has more). I naively tried to use -regress- but the dependent variable cannot be a factor variable and the data I have are not categorised in a continuous manner.
>>
>> Therefore, does anyone have any suggestions on how I might be able to model the effect of one of my variables (ethnicity or social deprivation) on stage at diagnosis?
>>
>> Any help gratefully received.
>>
>> Best wishes
>>
>> Tim
>>
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