Article citationsMore>>

Colzani, E., Liljegren, A., Johansson, A. L. V., Adolfsson, J., Hellborg, H., Hall, P. F. L., & Czene, K. (2011). Prognosis of patients with breast cancer: Causes of death and effects of time since diagnosis, age, and tumor characteristics. Journal of Clinical Oncology, 29, 4014- 4021. doi:10.1200/JCO.2010.32.6462

has been cited by the following article:

• TITLE: Modeling Time in Medical Education Research: The Potential of New Flexible Parametric Methods of Survival Analysis

  AUTHORS: Gilbert Reibnegger

  KEYWORDS: Study Dropout; Medical Studies; Survival Analysis; Flexible Parametric Models; Royston-Parmar Models

  JOURNAL NAME: Creative Education, Vol.3 No.6A, October 25, 2012

  ABSTRACT: Time – the duration of a certain process or the timing of a specified event – plays a central role in many situations in medical research. Waiting time analysis (“survival analysis”) is a field of statistics providing the tools for solving the unique problems of such studies. In particular, waiting time analysis correctly handles the typical positively skewed distributions of waiting times as well as censored observations on study subjects for whom the target event does not occur before data collection ends. For decades, non-parametric Kaplan-Meier analysis and semiparametric Cox regression despite some inherent limitations have dominated waiting time analysis in medical contexts, while parametric models, although in principle offering important theoretical advantages, were scarcely applied in practice because of lacking flexibility. Recently, however, new flexible parametric methods (Royston-Parmar models) became available offering exciting new research potential. Surprisingly, although medical education research deals with a range of typical problems suited for waiting time analysis, the methods were rarely used in the past. By re-analyzing data from a previous investigation on study dropout of medical students, this is the first study demonstrating the usefulness and practical applications of waiting time analysis with special emphasis on Royston-Parmar models in a medical education research environment.