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Re: FW: st: Regression with multiple age groups


From   David Hoaglin <[email protected]>
To   [email protected]
Subject   Re: FW: st: Regression with multiple age groups
Date   Wed, 25 Apr 2012 22:58:01 -0400

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 <[email protected]> wrote:
> Hi David,
> Thanks for your reply!
> 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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