The joint models for longitudinal and time-to-event data are a recentfamily of models that analyse jointly longitudinal and survival data. These modelsare composed of two sub-models, a hazard function related to the true and unob-served value of the longitudinal outcome, and a longitudinal mixed model where theoutcome is equal to the true level plus a random error term. Several authors appliedthis model to a biostatistic area, but this paper aims to analyse the timing of studentgraduation in an Italian university. The model will analyse jointly the time to grad-uation and the student’s path, focusing on the average grade and on the number ofexams that the student has already passed before a fixed time.
Mazzoleni, M., Zenga, M., Marshall, A. (2016). The Timing of Student Graduation: a Joint Model Approach. In J.R. Bozeman, T. Oliveira, C.H. Skiadas (a cura di), Stochastic and Data Analysis Methods and Applications in Statistics and Demography (pp. 61-74). ISAST.
The Timing of Student Graduation: a Joint Model Approach
Mazzoleni, M;Zenga M;
2016
Abstract
The joint models for longitudinal and time-to-event data are a recentfamily of models that analyse jointly longitudinal and survival data. These modelsare composed of two sub-models, a hazard function related to the true and unob-served value of the longitudinal outcome, and a longitudinal mixed model where theoutcome is equal to the true level plus a random error term. Several authors appliedthis model to a biostatistic area, but this paper aims to analyse the timing of studentgraduation in an Italian university. The model will analyse jointly the time to grad-uation and the student’s path, focusing on the average grade and on the number ofexams that the student has already passed before a fixed time.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.