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    請使用永久網址來引用或連結此文件: https://ir.lib.ncu.edu.tw/handle/987654321/105822


    題名: Joint model of multiple longitudinal measures and a binary outcome: An application to predict orthostatic hypertension for subacute stroke patients
    作者: 曾議寬;Hwang, Yi-Ting;Wang, Chun-Chao;Wang, Chiuan He;Tseng, Yi-Kuan;Chang, Yeu-Jhy
    貢獻者: 理學院統計研究所
    關鍵詞: Biometry - methods;Blood Pressure;General Medicine;Heart Rate;Humans;Hypertension;Hypertension - complications;Hypertension - diagnosis;Hypertension - physiopathology;Joint model;Logistic regression;Longitudinal Studies;Models, Statistical;Monte Carlo Method;Monte Carlo simulation;Multiple longitudinal measures;Orthostatic hypertension;Prognosis;Random effect model;Receiving operating characteristic curve;ROC Curve;Statistics and Probability;Statistics, Probability and Uncertainty;Stroke;Stroke - complications
    日期: 2015-01-01
    上傳時間: 2026-04-23 12:55:15 (UTC+8)
    出版者: Wiley-VCH Verlag;Germany: Blackwell Publishing Ltd
    摘要: 摘要: Stroke patients with orthostatic hypertensive responses that are one of the blood pressure regulation problems can easily fall down while doing rehabilitation, which may result in prolonged hospitalization and delayed treatment and recovery. This may result in increasing the medical cost and burden. In turn, developing a diagnostic test for the orthostatic hypertension (OH) is clinically important for patients who are suffering from stroke. Clinically, a patient needs to have a tilt testing that requires measuring the change of blood pressures and heart rate at all angles to determine whether a stroke patient has OH. It takes lots of time and effort to perform the test. Assuming there exist measurement errors when obtaining the blood pressures and heart rate at all angles, this paper proposes using multiple mixed‐effect models to obtain the true trajectories of these measurements, which take into account the measurement error and the possible correlation among multiple measurements, and a logistic regression uses these true trajectories at a given time and other fixed‐effect covariates as predictors to predict the status of OH. The joint likelihood function is derived to estimate parameters and the area under the receiver operating characteristics curve is used to estimate the predictive power of the model. Monte Carlo simulations are performed to evaluate the feasibility of the proposed methods. Also, the proposed model is implemented in the real data and provides an acceptable predictive power.
    其他題名: Biom. J
    出版者: Germany: Blackwell Publishing Ltd
    出版日期: 2015-07
    出處: Biometrical Journal, 2015-07, Vol.57 (4), p.661-675
    資源來源: Wiley Journals
    版權: 2015 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim
    版權: 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
    版權: 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
    識別號: ISSN: 0323-3847
    識別號: EISSN: 1521-4036
    識別號: DOI: 10.1002/bimj.201400044
    識別號: PMID: 25921394
    顯示於類別:[統計研究所] 期刊論文

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