General population samples provide recovery data for all alcohol dependent individuals, but most are cross-sectional. Although retrospectively ascertained cross-sectional data can identify fixed characteristics associated with recovery, e.g., sex, they preclude inferring causality for factors whose values vary over the life course. When the timing of these factors can be established, this limitation can be overcome through the use of pseudo-prospective time-dependent survival models. Using this approach, a study based on the 2001-2002 National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) showed that the likelihood of AR and NR increased after the initiation of alcohol treatment or 12-step participation (Dawson et al., 2006a). A similar study demonstrated that both initiating and terminating a first marriage increased the odds of NR within the first three years following these events, after which point those still dependent had a reduced likelihood of subsequent NR. The likelihood of AR was increased in the first three years after becoming a parent for the first time (Dawson et al., 2006b). Other examples of pseudo-prospective approaches utilizing general population samples include a study in which past-year
