[R-sig-ME] Modeling attacks and victories
dakotajudo at mac.com
Wed Apr 19 18:28:51 CEST 2017
This is just off the top of my head, but wouldn’t you model the response as a Poisson binomial?
My simple way of thinking about it would be that the number of attacks per year is a Poisson process, while the probability of success is binomial, and p is independent for country.
> On Apr 19, 2017, at 10:39 AM, Paul Johnson <pauljohn32 at gmail.com> wrote:
> Could I ask for pointers on how to guide a student in my multilevel
> modeling course?
> The outcome data is terrorist attack events, with one row per event
> (events are listed by country and year). The data also indicates if
> each attach is a "success" (I have no idea how that's measured, if it
> matters I can find out).
> The student says that, in his field, what they would do is aggregate
> events at the country/year level to create a "proportion of successful
> attacks" variable. If a country has no events, then it is scored as a
> 0. Then they'd run random intercept models using country as case
> identifier, possibly with other country level predictors that vary
> across time.
> I think we can do better than that. The number of events within
> countries varies widely, some have 0 or 1 attack, while in some years
> there are 30 or more. Measuring the proportions is, obviously,
> sensitive to the number in the denominator. Some countries are scored
> on a scale 0, .5, 1, while others are scored as 0, 0.03, 0.06, and so
> forth. Other obvious problems are the presence of 0's.
> My first idea was to made this a binomial glm and predict successes as
> a proportion of attacks. That's a problem because there are lots of 0
> attack country/years, but also because I'm
> It looks to me like we need to explore this as a two part model, where
> part 1 predicts (attacks > 0) and part 2 is binomial among the
> countries and places where attacks > 0. I'm not finding discussion of
> this particular example while searching (I probably don't know the
> magic words). However, we need to insert the country-level intercept
> in both models, and perhaps the country effect needs to be correlated
> between the two models.
> Paul E. Johnson http://pj.freefaculty.org
> Director, Center for Research Methods and Data Analysis http://crmda.ku.edu
> To write to me directly, please address me at pauljohn at ku.edu.
> R-sig-mixed-models at r-project.org mailing list
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