[R-sig-ME] logistic model with exponential decay
s.ruiter at maw.ru.nl
Sun Dec 21 22:09:14 CET 2008
Thanks David, I should look into that, but I usually estimate
discrete-time models which are basically logistic regression models on
person-years files with only the records included that are "at risk".
Anyway, do these packages also allow for nonlinear effects the way I
Department of Sociology / ICS
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David Duffy schreef:
> On Sun, 21 Dec 2008, Stijn Ruiter wrote:
>> I have official judicial data on criminal offending (dichotomous
>> dependent variable=conviction(=Y)) of all (adult) children of fathers
>> who differ with respect to their level of criminal behavior. These
>> data were registered on a yearly basis. So, I am able to follow
>> people over the course of their lives and model whether they get
>> convicted. I intend to estimate a discrete-time logit model on a
>> person-year file. Of course, because children are nested within their
>> fathers, I need to take that into account. Furthermore, many subjects
>> get convicted more than once during their lives, so I need to
>> estimate a repeated events model.
>> I have several time-constant variables (e.g., gender) and several
>> time-varying variables (e.g., number of years since father committed
>> a crime(=T)). I would like to estimate something like this:
>> logit(Y) ~ alpha + beta1*GENDER + exp(-T/beta2) + ... + error term
>> for nesting within fathers + error term for nesting within subject
> You also want the person-years at risk as an offset too, don't you?
> And do you have many families, so there are multiple individuals with
> the same father? You may know that the R survival package implements
> frailty models that would be applicable, and that the kinship package
> specifically offers a Cox proportional hazards model (with gaussian
> random effects) that can incorporate two crossed variance components.
> Cheers, David Duffy.
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