logistic model with exponential decay
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 Stijn
Best regards, Stijn Ruiter Department of Sociology / ICS Radboud University Nijmegen P.O. Box 9104 6500 HE Nijmegen Netherlands Phone: + 31 24 361 2272 Fax: + 31 24 361 2399 Visiting address: Thomas van Aquinostraat 4.01.71 Nijmegen website: http://oase.uci.ru.nl/~sruiter Douglas Bates schreef: > On Sun, Dec 21, 2008 at 4:00 AM, Stijn Ruiter <s.ruiter at maw.ru.nl> wrote: > >> Hi all, >> Frederik is right. Do you think such a model can be estimated using nlmer? >> > > >> How? >> > > We would need more detail about the data and the model to be able to answer. > > Is the response on a continuous scale (i.e. not binary or a count)? > > What are the covariates? > > What is the model for the mean response? > > How many random effects would be defined and how would they enter the > model for the mean response? >