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Modelling agreement for binary intensive longitudinal data
- Source :
- Statistical Modelling, 23(2):ARTN 1471082X211034002, 127-150. SAGE Publications Inc.
- Publication Year :
- 2023
-
Abstract
- 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.
- Subjects :
- Statistics and Probability
time-event sequential data
Science & Technology
Computer science
Longitudinal data
Statistics & Probability
Measure (physics)
Binary number
WEIGHTED KAPPA
PARAMETERS
Reliability engineering
transient event
Mental condition
Physical Sciences
RELIABILITY
Continuous recording
Statistics, Probability and Uncertainty
time series
COEFFICIENT
Reliability (statistics)
Mathematics
continuous recording
Subjects
Details
- Language :
- English
- ISSN :
- 1471082X
- Database :
- OpenAIRE
- Journal :
- Statistical Modelling, 23(2):ARTN 1471082X211034002, 127-150. SAGE Publications Inc.
- Accession number :
- edsair.doi.dedup.....85c3a519127424f0a441878b5ef55315