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It’s About Time: Using Discrete-Time Survival Analysis to Study Duration and the Timing of Events

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  • Judith D. Singer
  • John B. Willett

Abstract

Educational researchers frequently ask whether and, if so, when events occur. Until relatively recently, however, sound statistical methods for answering such questions have not been readily available. In this article, by empirical example and mathematical argument, we demonstrate how the methods of discrete-time survival analysis provide educational statisticians with an ideal framework for studying event occurrence. Using longitudinal data on the career paths of 3,941 special educators as a springboard, we derive maximum likelihood estimators for the parameters of a discrete-time hazard model, and we show how the model can befit using standard logistic regression software. We then distinguish among the several types of main effects and interactions that can be included as predictors in the model, offering data analytic advice for the practitioner. To aid educational statisticians interested in conducting discrete-time survival analysis, we provide illustrative computer code ( SAS, 1989 ) for fitting discrete-time hazard models and for recapturing fitted hazard and survival functions.

Suggested Citation

  • Judith D. Singer & John B. Willett, 1993. "It’s About Time: Using Discrete-Time Survival Analysis to Study Duration and the Timing of Events," Journal of Educational and Behavioral Statistics, , vol. 18(2), pages 155-195, June.
    • Handle: RePEc:sae:jedbes:v:18:y:1993:i:2:p:155-195
    DOI: 10.3102/10769986018002155
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    Cited by:

    1. Kelly J. Tiller & Shiferaw T. Feleke & Jane H. Starnes, 2010. "A discrete‐time hazard analysis of the exit of burley tobacco growers in Tennessee, North Carolina, and Virginia," Agricultural Economics, International Association of Agricultural Economists, vol. 41(5), pages 397-408, September.
    2. Rose, Damaris & Stavrova, Olga, 2019. "Does life satisfaction predict reemployment? Evidence form German panel data," Journal of Economic Psychology, Elsevier, vol. 72(C), pages 1-11.
    3. Subramanian, S.V. & Elwert, Felix & Christakis, Nicholas, 2008. "Widowhood and mortality among the elderly: The modifying role of neighborhood concentration of widowed individuals," Social Science & Medicine, Elsevier, vol. 66(4), pages 873-884, February.
    4. Xiao, Jing, 2018. "Post-acquisition dynamics of technology start-ups: drawing the temporal boundaries of post-acquisition restructuring process," Papers in Innovation Studies 2018/12, Lund University, CIRCLE - Centre for Innovation Research.
    5. Sena Kimm GNANGNON, 2012. "An analysis of duration dependence of government revenue expansions and contractions in Developing Countries," Working Papers 201229, CERDI.
    6. Khataza, Robertson R.B. & Doole, Graeme J. & Kragt, Marit E. & Hailu, Atakelty, 2018. "Information acquisition, learning and the adoption of conservation agriculture in Malawi: A discrete-time duration analysis," Technological Forecasting and Social Change, Elsevier, vol. 132(C), pages 299-307.
    7. Raffaele Santioni & Fabio Schiantarelli & Philip E. Strahan, 2017. "Internal Capital Markets in Times of Crisis: The Benefit of Group Affiliation in Italy," Boston College Working Papers in Economics 929, Boston College Department of Economics, revised 20 Aug 2019.
    8. Zdravko Šergo & Jasmina Gržiniæ & Mirela Suèiæ Èevra, 2017. "The tourism and travel industry and its effect on the Great Recession: A multilevel survival analysis," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 35(2), pages 427-458.
    9. Chandrasekaran, Deepa & Arts, Joep W.C. & Tellis, Gerard J. & Frambach, Ruud T., 2013. "Pricing in the international takeoff of new products," International Journal of Research in Marketing, Elsevier, vol. 30(3), pages 249-264.
    10. Bettina Lamla, 2012. "Family Background, Informal Networks and the Decision to Provide for Old Age: A Siblings Approach," SOEPpapers on Multidisciplinary Panel Data Research 466, DIW Berlin, The German Socio-Economic Panel (SOEP).
    11. Scharfenkamp, Katrin, 2018. "The effects of bridging business and politics – A survival analysis of German Federal ministers," European Journal of Political Economy, Elsevier, vol. 55(C), pages 433-454.
    12. repec:mea:meawpa:12261 is not listed on IDEAS
    13. Legoux, Renaud & Larocque, Denis & Laporte, Sandra & Belmati, Soraya & Boquet, Thomas, 2016. "The effect of critical reviews on exhibitors' decisions: Do reviews affect the survival of a movie on screen?," International Journal of Research in Marketing, Elsevier, vol. 33(2), pages 357-374.
    14. Hee-Koung Joeng & Ming-Hui Chen & Sangwook Kang, 2016. "Proportional exponentiated link transformed hazards (ELTH) models for discrete time survival data with application," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 22(1), pages 38-62, January.
    15. Cristian Ionel Rotaru, 2014. "Transitioning Out of Unemployment: Analysis Using the ABS Longitudinal Labour Force Survey File," Australian Journal of Labour Economics (AJLE), Bankwest Curtin Economics Centre (BCEC), Curtin Business School, vol. 17(2), pages 111-137.
    16. Brad N. Greenwood & Ritu Agarwal, 2016. "Matching Platforms and HIV Incidence: An Empirical Investigation of Race, Gender, and Socioeconomic Status," Management Science, INFORMS, vol. 62(8), pages 2281-2303, August.
    17. Sèna Kimm Gnangnon, 2012. "An analysis of duration dependence of government revenue expansions and contractions in Developing Countries," Working Papers halshs-00722083, HAL.
    18. Maryam Safarkhani & Shahab Jolani & Mirjam Moerbeek, 2014. "Optimal number of accrual groups and accrual group sizes in longitudinal trials with discrete-time survival endpoints," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 68(1), pages 43-60, February.
    19. Maryam Safarkhani & Mirjam Moerbeek, 2016. "D-optimal designs for a continuous predictor in longitudinal trials with discrete-time survival endpoints," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 70(2), pages 146-171, May.
    20. Catalina A. Vallejos & Mark F. J. Steel, 2017. "Bayesian survival modelling of university outcomes," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(2), pages 613-631, February.
    21. Kathleen L. McGinn & Katherine L. Milkman, 2013. "Looking Up and Looking Out: Career Mobility Effects of Demographic Similarity Among Professionals," Organization Science, INFORMS, vol. 24(4), pages 1041-1060, August.
    22. Robert M. Groves & Steven G. Heeringa, 2006. "Responsive design for household surveys: tools for actively controlling survey errors and costs," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(3), pages 439-457, July.
    23. Jeffrey A. Groen, 2016. "The Impact of Labor Demand on Time to the Doctorate," Education Finance and Policy, MIT Press, vol. 11(1), pages 43-69, Winter.

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