Abstract: Recurrent event data and gap times between recurrent events are often the targets in the analysis of longitudinal follow-up or epidemiological studies. To analyze the gap times, Huang and Chen (2003), among others, proposed to fit the proportional hazards model. It is well-known, however, that the proportional hazards model might not fit the data well. To provide an alternative, this paper investigates the fit of the additive hazards model to gap time data, and an estimating equation approach is presented for inference about regression parameters. Both asymptotic and finite sample properties of the proposed parameter estimates are established. One major advantage of the use of the additive hazards model over the proportional hazards model is that the resulting parameter estimator has a closed form. The method is applied to a cancer study.
Key words and phrases: Additive hazards model, estimating equations, gap time, recurrent event data, regression analysis.