Event History Analysis
Event History Analysis (EHA) allows researchers to examine the determinants or factors behind the occurrence of events over time. EHA is applied to longitudinal data and allows the research to control for time varying covariates.
An ‘event’ (the dependent variable in an EHA) is a change from one state to another and is measured as a categorical/discrete variable. The methodology is increasingly being used by researchers across a large range of disciplines with developments in computer software programmes such as STATA, SPSS and SAS.
Research question examples
Examples of research questions which can be examined using event history analyses include:
- Does gang membership increase recidivism?
REF: Caudill, J. W. (2010) Back on the Swagger: Institutional Release and Recidivism Timing Among Gang Affiliates. Youth Violence and Juvenile Justice 8: 58-70
- What increases or decreases fixed-term contract workers’ chances of getting a permanent job?
REF: Gash V. (2008) “Bridge or Trap? To what extent do temporary workers make more transitions to unemployment than to the standard employment contract”. European Sociological Review, 24(5): 651-668.
- What is the effect of a husband’s employment status on women’s labour market outcomes?
REF: McGinnity, F. (2002) ‘The Labour-force Participation of the Wives of Unemployed Men: Comparing Britain and West Germany Using Longitudinal Data’, European Sociological Review, 18: 473- 488.#
Users of Event History Analysis at Manchester
Useful introductory readings on Event History Analysis
- Allison, P.D. 1984. Event History Analysis: Regression for Longitudinal Event Data. Beverley Hills: Sage.
- Blossfeld, H-P, Golsch, K. and G. Rohwer. 2007. Event History Analysis with Stata. Mawah, NJ: Lawrence Erlbaum Associates
- Castilla, E. (2007) Dynamic Analysis in the Social Sciences. London: Elsevier
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