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Using maximum simulated likelihood methods to overcome left censoring: Dynamic event history models of heart attack risk in New Zealand

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  • Sanghyeok Lee
  • Tue Gørgens

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.

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  • Sanghyeok Lee & Tue Gørgens, 2022. "Using maximum simulated likelihood methods to overcome left censoring: Dynamic event history models of heart attack risk in New Zealand," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(1), pages 348-376, January.
    • Handle: RePEc:bla:jorssa:v:185:y:2022:i:1:p:348-376
    DOI: 10.1111/rssa.12758
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