Using Maximum Simulated Likelihood Methods to Overcome Left Censoring: Dynamic Event History Models of Heart Attack Risk in New Zealand
本文利用新西兰行政数据，通过最大模拟似然方法处理左删失数据，估计动态风险模型，发现首次心脏病发作后一年内复发风险极高，且毛利人风险高于欧裔。
Abstract This paper describes how the risk of experiencing heart attacks varies across gender and ethnicity in New Zealand. We estimate dynamic hazard models using administrative data. We deal with left-censored data using recently developed maximum simulated likelihood methods. The models allow risk to vary with age, previous heart attack history and unobserved individual heterogeneity. We find that the risk of subsequent events is far higher than the risk of the first event, particularly high within 1 year after an event, and that unobserved heterogeneity is important. Generally, male Maoris have the highest risk, followed by female Maoris, then ethnically European males, while ethnically European females have the lowest risk.