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# RE: st: Regression with multiple age groups

 From Shirley Sy To Subject RE: st: Regression with multiple age groups Date Fri, 27 Apr 2012 15:35:36 +0100

```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
----------------------------------------
> Date: Wed, 25 Apr 2012 22:58:01 -0400
> Subject: Re: FW: st: Regression with multiple age groups
> From: dchoaglin@gmail.com
> To: statalist@hsphsun2.harvard.edu
>
> Hi, Shirley.
>
> Thanks for the additional information!
>
> I can see difficulties in that way of calculating a divorce rate. For
> example, the number of marriages in a given year is probably not a
> good measure of the number of marriages that are at risk of divorce.
>
> I don't yet understand what the individual observations are in your
> data. Many of the explanatory variables suggest that the observations
> are individual divorces (e.g., husband's age, wife's age, duration of
> marriage). The unemployment rates might be constant by year. I'm not
> sure what to make of the average number of children per couple; what
> is being averaged over?
>
> If the observations are individual divorces, I don't think you have an
> analysis of divorce rates. You may be able to analyze how the
> characteristics of the divorcing couple change over time. That
> analysis is more likely to involve techniques for categorical
> variables than it is to involve regresssion. What questions would you
> like the analysis to answer?
>
> David Hoaglin
>
> On Wed, Apr 25, 2012 at 11:21 AM, Shirley Sy <shirleysy@hotmail.co.uk> wrote:
> > Hi David,
> > I took the data from the Office of National Statistics website for the years 1980 to 2000. My independent variable is the divorce rate (which I calculated myself using the total number of divorces in a given year divided by the total number of marriages in the same year) and my explanatory variables are: husband's age at divorce, wife's age at divorce, husband's previous marital status, wife's previous marital status, combination of husband's and wife's previous marital status (i.e. first marriage for both, one party previously divorced, both previously divorced), duration of marriage (under 2yrs, 2-5, 6-9, 10-14, 15-19, 20-24, 25-29, 30+, not stated), average number of children per couple, female unemployment rate and male unemployment rate.
> > I was planning to do OLS and have not considered poisson or negative binomial as of yet. Unfortunately I was given this project to do without any supervision and absolute minimal help and I was only taught the very basics of Stata a year ago so I didn't intend on doing other models with the fear of doing it completely wrong. Would an ARIMA model be appropriate for this data? Shirley
>
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