Modeling Bivariate Longitudinal Hormone Profiles by Hierarchical State Space Models

The hypothalamic-pituitary-adrenal (HPA) axis is crucial in coping with stress and maintaining homeostasis. Hormones produced by the HPA axis exhibit both complex univariate longitudinal profiles and complex relationships among different hormones. Consequently, modeling these multivariate longitudin...

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Vydané v:	Journal of the American Statistical Association Ročník 109; číslo 505; s. 108 - 118
Hlavní autori:	Liu, Ziyue, Cappola, Anne R., Crofford, Leslie J., Guo, Wensheng
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States Taylor & Francis 2014 Taylor & Francis Group, LLC Taylor & Francis Ltd
Predmet:	Algorithms Applications and Case Studies Brain Chronic fatigue syndrome Circadian rhythm Complexity Coping corticotropin Cortisol Data smoothing Disease models Feedback Feedback relationship Fibromyalgia Hierarchies Homeostasis Hormones HPA axis Hypothalamic-pituitary-adrenal axis Inference Kalman filter Kalman filters Multilevel models Nonparametric models patients Periodic splines Profiles Statistical discrepancies Statistics Stress Time series analysis Time series models Feedback Relationship HPA axis Periodic splines Circadian rhythm Kalman filter
ISSN:	1537-274X, 0162-1459, 1537-274X
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