The gap time between recurrent events is often of primary interest in many ?elds such as medical studies (Cook and Lawless, 2007; Kang et al., 2015; Schaubel and Cai, 2004) and in this paper, we discuss regression analysis of the gap times arising from a general class of additive transformation models. For the problem, we propose two estimation procedures, the modi?ed within-cluster resampling (MWCR) method and the weighted risk-set (WRS) method, and the proposed estimators are consistent and asymptotically follow the normal distribution. In particular, the estimators have closed forms and can be easily determined. A simulation study is conducted for assessing the ?nite sample performance of the presented methods and suggests that they work well in practical situations. Also the methods are applied to a set of real data from a chronic granulomatous disease (CGD) clinical trial.