  We consider parameter estimation in a regression model corresponding to an
iid sequence of censored observations of a finite state modulated renewal
process. The model assumes a similar form as in Cox regression except that the
baseline intensities are functions of the backwards recurrence time of the
process and a time dependent covariate. As a result of this it falls outside
the class of multiplicative intensity models. We use kernel estimation to
construct estimates of the regression coefficints and the baseline cumulative
hazards. We give conditions for consistency and asymptotic normality of
estimates. Data from a bone marrow transplant study are used to illustrate the
results.
