Quality & Quantity

, Volume 47, Issue 5, pp 2425–2446 | Cite as

Dropout in secondary education: an application of a multilevel discrete-time hazard model accounting for school changes

  • Carl Lamote
  • Jan Van Damme
  • Wim Van Den Noortgate
  • Sara Speybroeck
  • Tinneke Boonen
  • Jerissa de Bilde


For several decades, researchers have focused on dropout in search for an explanation and prevention of this phenomenon. However, past research is characterized by methodological shortcomings. Most of this research was conducted without considering the hierarchical structure of educational data and ignored the longitudinal path towards dropout. Moreover, research that did take into account these shortcomings, did not correct for student mobility between schools, despite the strong correlation with dropout (South et al. 2007). In this study, we attempt to address these shortcoming by implementing a multilevel discrete-time hazard model and exploring the effect of different school classifications on the school effects. Partially analogous to Grady and Beretvas (2010) we compare models with estimated school effects based on the first and on the last school attended and compare these models with multiple membership models and cross-classified models. The results of this comparison indicate that ignoring student mobility can have strong implications on the predictors of dropout. Not only do models which take into account this mobility yield better model fits, models ignoring this mobility tend to miss the effect of school level variables. With respect to the conclusions on dropout research, our models provide evidence for the often cited student characteristics predicting dropout and indicate stronger school effects than generally assumed.


Discrete-time hazard analysis Cross-classifications Multiple membership Dropout Secondary education Methodology of longitudinal research 



Deviance Information Criterion


‘Longitudinaal Onderzoek in het Secundair Onderwijs’ or ‘Longitudinal research in secondary education’


Markov Chain Monte Carlo


Multilevel discrete-time hazard analysis


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Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  • Carl Lamote
    • 1
  • Jan Van Damme
    • 1
  • Wim Van Den Noortgate
    • 2
  • Sara Speybroeck
    • 1
  • Tinneke Boonen
    • 1
  • Jerissa de Bilde
    • 1
  1. 1.Centre for Educational Effectiveness and EvaluationThe Education and Training Research Group, K. U. LeuvenLeuvenBelgium
  2. 2.Methodology of Educational Sciences Research Group, K. U. LeuvenLeuvenBelgium

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