Modelling agreement for binary intensive longitudinal data

S. Vanbelle*, E. Lesaffre

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


Devices that measure our physical, medical and mental condition have entered our daily life recently. Such devices measure our status in a continuous manner and can be useful in predicting future medical events or can guide us towards a healthier life. It is therefore important to establish that such devices record our behaviour in a reliable manner and measure what we believe they measure. In this article, we propose to measure the reliability and validity of a newly developed measuring device in time using a longitudinal model for sequential kappa statistics. We propose a Bayesian estimation procedure. The method is illustrated by a validation study of a new accelerometer in cardiopulmonary rehabilitation patients.
Original languageEnglish
Article numberARTN 1471082X211034002
Number of pages24
JournalStatistical Modelling
Publication statusE-pub ahead of print - 3 Sep 2021


  • continuous recording
  • Reliability
  • time-event sequential data
  • time series
  • transient event

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