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Re: st: Comparing trend (y) with trend (x) using ordinal logistic regression


From   Nick Cox <njcoxstata@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Comparing trend (y) with trend (x) using ordinal logistic regression
Date   Mon, 12 Nov 2012 19:12:17 +0000

I'd follow Maarten's pointers on this. Yes; -bf- can be a predictor too.

I am puzzled by your belief, repeated here, that you need new
variables. You already have the data in optimal form as 0 and 1 values
for logit analyses: creating different versions of the same variables
will make nothing easier and -logit- impossible.

Nick

On Mon, Nov 12, 2012 at 6:59 PM, Ameya Bondre
<ameyabondre.jhsph@gmail.com> wrote:
> Thanks, I am trying to see if I can adapt the example given by
> Maarten, to my data...but would it be possible if I want to include
> mal and bf as a response and predictor respectively, in the same logit
> model and with this data set?
>
> If yes, do I have to create new variables from mal and bf, to see
> trend in mal as a function of trend in bf?
>
>  I mean variables such as mal = 1 (mal in 2009) or 2 (mal in 2011) and
> bf = 1 (bf in 2009) or 2  (bf in 2011)
>
>
> On Mon, Nov 12, 2012 at 1:35 PM, Nick Cox <njcoxstata@gmail.com> wrote:
>>
>> All your variables are binary, so your ordinal logit collapses to a
>> logit. Other predictors you don't name won't change that so long as
>> your outcome variable is fraction or proportion malnourished.
>>
>> Nick
>>
>> On Mon, Nov 12, 2012 at 6:17 PM, Ameya Bondre
>> <ameyabondre.jhsph@gmail.com> wrote:
>>
>> > My data set is in this format: [observations 1 to 6 --> children (with
>> > their mothers as respondents)]
>> >
>> >         mal     bf      time
>> > 1       0       0       0
>> > 2       1       0       0
>> > 3       1       1       0
>> > 4       0       1       1
>> > 5       0       1       1
>> > 6       1       0       1
>> >
>> > where each of the three variables is ordinal taking two values, 0 and 1.
>> >
>> > Explanation for variables:
>> >
>> > time: data collected in year ___ (0 = year 2009, 1 = year 2011)
>> > mal: child malnourished (0 = no, 1 = yes)
>> > bf: child breastfed exclusively for first six months (0 = no, 1 = yes)
>> >
>> > I want to see the relationship between the change in number of
>> > malnourished children with the change in number of children
>> > exclusively breastfed, from 2009 to 2011. I tried to perform an
>> > ordinal logistic regression but I am getting errors.
>> >
>> > Could you please explain the way in which I can construct new
>> > variables out of these, to enter in the ologit model? My end goal is
>> > to assess the change in malnutrition as a function of the change in
>> > other predictors as well, in addition to bf.
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