Re: analyzing change for one dichotomous variable, assessed at pre and post

Posted by Rich Ulrich on May 06, 2012; 9:12pm
URL: http://spssx-discussion.165.s1.nabble.com/analyzing-change-for-one-dichotomous-variable-assessed-at-pre-and-post-tp5688136p5689730.html

Create a test using these data alone? (No rates available
as norms.)

No, there is no interesting test available.

If you had half the smokers quit, that would seem to me to
be a "large number" -- depending on ages and years of gap --
but there is nothing available to say that it is "unexpected"
and should be anything other than a curious sample/ population
statistic.

And I would see no reason to expect the number quitting
to match the number starting, which is the null hypothesis
of McNemar's test.

--
Rich Ulrich

> Date: Sat, 5 May 2012 09:21:17 -0700

> From: [hidden email]
> Subject: analyzing change for one dichotomous variable, assessed at pre and post
> To: [hidden email]
>
> I have a situation where I have one variable, smoking yes/no, taken at pre
> then taken at post, few years later. n ~70. same participants at both pre
> and post. the possible combinations are
>
> smoking pre post
> y y
> n n
> y n
> n y
>
> goal is to determine if the percentage of participants who changed from Y
> smoking at pre to N smoking at post is significant.
>
> I don't think any sophisticated analysis has to be conducted. I would simply
> assign the four possible outcomes to four categories (y - y, n - n, y - n, n
> - y) and then run a chi-square to determine if the observed frequency counts
> of those four categories are different from the expected frequency counts.
> there is no post-hoc test, so I would have to heuristically examine which
> categories have the most deviance.
>
> are there any analyses that could be conducted?

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