More specifically, survival analysis is designed to model the risk of onset, also known as hazard. The hazard can be modeled for continuous or for discrete time. Due to the character of the Add Health data (reported year of first use), discrete time survival models are more adequate. Discrete time survival models have been described in detail in Vermunt (1996), and Muthén and Masyn (2005). In essence, discrete time survival models serve to investigate the predictors of the risk of initiating a behavior. In this study, eight discrete age intervals were defined to correspond to reported first year of use and to ensure a sufficient number of subjects within each group: 5 ≤ 10, 10 ≤ 12, 13, 14, 15,16, 17, ≥18.
