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Discrete-time event history analysis using segmented hazards.

W Gardner1, M Meyer, R Ketterlinus

  • 1University of Virginia.

Experimental Aging Research
|January 1, 1991
PubMed
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This study introduces advanced event history analysis methods for discrete-time data and complex age-dependencies in aging and human development research. It enhances the analysis of life event timing using segmented hazards for more accurate insights.

Area of Science:

  • Demography
  • Sociology
  • Biostatistics

Background:

  • Event history analysis is crucial for understanding life event timing.
  • Studies in aging and human development face challenges with discrete time data and complex age-dependent event probabilities.

Purpose of the Study:

  • To present methods for estimating discrete-time event history models from continuous-time specifications.
  • To introduce segmented hazards for modeling complex age-dependencies in life events.

Main Methods:

  • Developed methods to estimate discrete-time event history models based on continuous-time specifications.
  • Constructed models using segmented hazards, combining different functions across time segments.
  • Applied methods to analyze the age of first intercourse in a large cohort.

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Main Results:

  • Successfully estimated discrete-time models from continuous-time specifications.
  • Demonstrated the utility of segmented hazards in capturing complex age-dependent patterns.
  • Provided insights into the timing of first intercourse using enhanced event history analysis.

Conclusions:

  • The proposed methods effectively address challenges in applying event history analysis to discrete-time data.
  • Segmented hazards offer a flexible approach to model intricate age-dependencies in life course events.
  • These advancements improve the analysis of aging and human development studies.