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A training manual for event history analysis using longitudinal data.

Philippe Bocquier1,2, Carren Ginsburg3, Mark A Collinson3,4

  • 1Centre de Recherche en Démographie, Université Catholique de Louvain, Place Montesquieu, 1 bte L2.08.03, 1348, Louvain-la-Neuve, Belgium. philippe.bocquier@uclouvain.be.

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Summary

This study presents tools for longitudinal event history analysis on Health and Demographic Surveillance System (HDSS) data. These methods streamline complex analyses, making demographic event data more accessible for researchers.

Keywords:
Demographic ratesEvent history analysisHealth and Demographic Surveillance SystemLongitudinal data analysis

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Area of Science:

  • Demography
  • Public Health
  • Epidemiology

Background:

  • Longitudinal data analysis is crucial for understanding demographic event dynamics.
  • Standardized Health and Demographic Surveillance System (HDSS) datasets offer valuable resources.
  • The Multi-centre Analysis of the Dynamics of Internal Migration And Health (MADIMAH) project addresses the need for robust analytical tools.

Purpose of the Study:

  • To collate and test tools for longitudinal event history analyses.
  • To apply these tools to standardized HDSS datasets.
  • To demonstrate streamlined and accessible methods for analyzing demographic event data.

Main Methods:

  • Utilizing longitudinal micro-data from the Agincourt HDSS.
  • Applying a set of validated tools for event history analysis.
  • Illustrating methods with detailed, tested computer programs.

Main Results:

  • The demonstrated methods are applicable to HDSS, retrospective survey, and register data.
  • Computer programs facilitate the generation of cross-sectional and longitudinal estimates.
  • Complex regression estimates can be effectively produced.

Conclusions:

  • The MADIMAH project successfully developed and tested tools for longitudinal data analysis.
  • These tools enhance the accessibility and efficiency of analyzing demographic event data.
  • The methods empower researchers to conduct sophisticated analyses on various longitudinal datasets.