logistic model with exponential decay
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.
| David Duffy (MBBS PhD) ,-_|\ | email: davidD at qimr.edu.au ph: INT+61+7+3362-0217 fax: -0101 / * | Epidemiology Unit, Queensland Institute of Medical Research \_,-._/ | 300 Herston Rd, Brisbane, Queensland 4029, Australia GPG 4D0B994A v