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Change-Point Estimates in Longitudinal Binary Data

Change-Point Estimates in Longitudinal Binary Data
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摘要 Most change-point models assume that the response is continuous or cross sectional binary. However, in many public health problems, the data is longitudinal binary. There are few studies of change-point problems for longitudinal outcomes. This paper describes a flexible change-point model which includes random-effects and takes into account the difference between various individuals in longitudinal binary data. A transition function is used to make the linear-linear logistic model differentiable at the change-point. The location of the change-point is estimated using the maximum likelihood method. Adjustment of the transition parameter from zero to one controls the sharpness of the transition. The performance of this estimation procedure is illustrated with simulations using SAS/proc nlmixed and a detailed analysis of data relating hormone levels and ovary functions based on data from the Obstetrics and Gynecology Hospital, Medical Center of Fudan University. Most change-point models assume that the response is continuous or cross sectional binary. However, in many public health problems, the data is longitudinal binary. There are few studies of change-point problems for longitudinal outcomes. This paper describes a flexible change-point model which includes random-effects and takes into account the difference between various individuals in longitudinal binary data. A transition function is used to make the linear-linear logistic model differentiable at the change-point. The location of the change-point is estimated using the maximum likelihood method. Adjustment of the transition parameter from zero to one controls the sharpness of the transition. The performance of this estimation procedure is illustrated with simulations using SAS/proc nlmixed and a detailed analysis of data relating hormone levels and ovary functions based on data from the Obstetrics and Gynecology Hospital, Medical Center of Fudan University.
作者 吴筱如 杨瑛
出处 《Tsinghua Science and Technology》 SCIE EI CAS 2008年第4期553-559,共7页 清华大学学报(自然科学版(英文版)
基金 the National Natural Science Foundation of China (Nos. 10671106 and 10731010)
关键词 CHANGE-POINT dichotomous outcome mixed-effects models logistic regression change-point dichotomous outcome mixed-effects models logistic regression
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