Modelling agreement for binary intensive longitudinal data

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