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Preface to the Revised Edition

New sections describe Stata’s ability to graph nonparametric and semiparametric estimates of hazard functions. Stata now calculates estimated hazards as weighted kernel-density estimates of the times at which failures occur, where weights are the increments of the estimated cumulative hazard function. These new capabilities are described in terms of nonparametric estimation in Chapter 8 and in terms of Cox regression (Chapter 9). Another added section in Chapter 9 discusses Stata’s ability to apply shared frailty to the Cox model. This section complements the discussion of parametric shared and unshared frailty models in Chapter 8. Because the frailty is best understood by beginning with a parametric model, this new section is relatively brief and focuses only on practical issues of estimation and interpretation.