Since the principal objective is to determine whether there are age-varying effects of the predictive variables, survival analysis using standard Cox proportional hazards models in which effects are age invariant is not appropriate. In addition, such models cannot account for differential effects on survival which are the result of unmeasured heterogeneity in the sample (frailty effects) (Wienke, 2007). Discrete time survival analysis (DTSA) (Singer and Willett, 1993; Willett and Singer, 1993; Rodriguez, 2007) provides an alternative model which avoids these problems and which can be implemented with logistic regression methods. By dividing subjects into groups based upon age of onset, a single logistic regression model can be applied to estimate the probability of those at risk in each age group of becoming alcohol dependent (or whatever other outcome is of interest) as a function of the predictive variables (covariates). The functional form of the model can be set to determine age-specific effects and/or age-independent effects, and use age-invariant and/or age-dependent covariates. A weighted model was employed to enable the use of all members of multi-member families (See section 6.1 for
