Modelling agreement for binary intensive longitudinal data
| Autor: | Sophie Vanbelle, Emmanuel Lesaffre |
|---|---|
| Přispěvatelé: | RS: CAPHRI - R6 - Promoting Health & Personalised Care, FHML Methodologie & Statistiek |
| Jazyk: | angličtina |
| Rok vydání: | 2023 |
| Předmět: |
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 |
| Zdroj: | Statistical Modelling, 23(2):ARTN 1471082X211034002, 127-150. SAGE Publications Inc. |
| ISSN: | 1471-082X |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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