[R-sig-ME] logistic model with exponential decay

Stijn Ruiter 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 
need them?

Best regards,

Stijn Ruiter
Department of Sociology / ICS
Radboud University Nijmegen
P.O. Box 9104
6500 HE Nijmegen

Phone: + 31 24 361 2272
Fax:   + 31 24 361 2399

Visiting address:
Thomas van Aquinostraat 4.01.71

website: http://oase.uci.ru.nl/~sruiter

David Duffy schreef:
> On Sun, 21 Dec 2008, Stijn Ruiter wrote:
>> Hi,
>> 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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