RE: st: Regression with multiple age groups

[Shirley Sy <shirleysy@hotmail.co.uk>]

Hi David,Thanks for your replies, which have been very helpful! The stage I am stuck on is dealing with the number of categorical variables I have. For example, say all I wanted to do was run a simple poisson regression with the data I have, how would I go about doing so when I have multiple subgroups for certain variables (i.e. husband's/wife's previous marital status, husband's/wife's age at divorce, duration of marriage) that contain count data of the total number of divorces in that year (spanning over 20 years) rather than individual level data?I've looked online extensively but can only find examples of individual level data or examples which are only applicable to one year and one categorical variable. I tried to run poisson regressing the total number of divorces against all the variables I have and a large number of variables were 'omitted because of collinearity' and I'm unsure of what step to take next.Thanks in advance! 
 
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> Date: Tue, 1 May 2012 09:29:27 -0400
> Subject: Re: st: Regression with multiple age groups
> From: dchoaglin@gmail.com
> To: statalist@hsphsun2.harvard.edu
>
> Hi, Shirley.
>
> Thanks for that link. I have not studied the data (for 2010) in
> detail, but the data on age at marriage of the husband and the wife
> involved in the divorce (or annulment) may give an indication of what
> you have to work with. The table on age of marriage cross-classifies
> the 119,589 divorces in England and Wales in 2010 by the age at
> marriage of the husband and the age at marriage of the wife, using the
> categories that you mentioned earlier. If you have such a crosstab for
> each of 20 years, you could analyze the behavior of the marginal
> distributions (husband's age, wife's age) over time, and also analyze
> the asssociation between those two ordered categorical variables over
> time.
>
> Two other tables cross-classify the duration of marriage at divorce by
> age of wife (resp. husband) at marriage. And the data file contains
> other tabulations.
>
> It's not clear to me how such crosstabs relate to the main goal of
> your project, forecasting divorce rates, but I am a statistician, not
> a demographer. Do demographers (or sociologists) use a standard
> definition of "divorce rate"? Earlier I expressed concern about using
> the number of marriages in the same year for the denominator. If you
> had divorce rates (using a standard definition), perhaps disaggregated
> by such characteristics as age of husband and age of wife, you might
> be able to model the behavior of the characteristics and combine the
> results with other variables (such as female unemployment rate and
> male unemployment rate, but for the current year or going back a year
> or two?) to predict divorce rates.
>
> Apart from any computing, it would be helpful to write out a "model"
> that relates divorce rate to the data that you have available, as a
> basis for understanding what's feasible. That model might not be the
> same as either of the two forecasting models. The variation in
> divorce rates is probably related to some of the available variables,
> but that relation does not necessarily mean that those variables
> "explain" the variation in divorce rates.
>
> David Hoaglin
>
> On Fri, Apr 27, 2012 at 10:35 AM, Shirley Sy <shirleysy@hotmail.co.uk> wrote:
> > Hi David,
> > For individual observations, say for husband's and wife's age, I have the total number of divorces in a particular year where the husband/wife was 'under20', '20to29' etc... and for duration of marriage, each subgroup has the total number of divorces that lasted 'under 2years', '2to5years' etc...
> > Just in case my explanation is poor, here's the link to the data that I am using: http://www.ons.gov.uk/ons/publications/re-reference-tables.html?edition=tcm%3A77-238035
> > My project is basically to try and explain the variation in divorce rates over time given the available data I have and compare the use of two forecasting models. Apologies for my poor knowledge on regression, I know a lot of theory and very little practical application of it.
> > Shirley
>
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