caa a22 4500 475826620 CHVBK 20180406123830.0 cr unu---uuuuu 170329e20000901xx s 000 0 eng 10.1023/A:1004125621021 doi (NATIONALLICENCE)springer-10.1023/A:1004125621021 A Two-Step Smoothing Method for Varying-Coefficient Models with Repeated Measurements [Elektronische Daten] [Colin Wu, Kai Yu, Chin-Tsang Chiang] Datasets involving repeated measurements over time are common in medical trials and epidemiological cohort studies. The outcomes and covariates are usually observed from randomly selected subjects, each at a set of possibly unequally spaced time design points. One useful approach for evaluating the effects of covariates is to consider linear models at a specific time, but the coefficients are smooth curves over time. We show that kernel estimators of the coefficients that are based on ordinary local least squares may be subject to large biases when the covariates are time-dependent. As a modification, we propose a two-step kernel method that first centers the covariates and then estimates the curves based on some local least squares criteria and the centered covariates. The practical superiority of the two-step kernel method over the ordinary least squares kernel method is shown through a fetal growth study and simulations. Theoretical properties of both the two-step and ordinary least squares kernel estimators are developed through their large sample mean squared risks. The Institute of Statistical Mathematics, 2000 Bandwidth nationallicence kernel nationallicence longitudinal data nationallicence mean squared error nationallicence ultrasound measurement nationallicence varying coefficient models nationallicence Wu Colin Department of Mathematical Sciences, The Johns Hopkins University, 21218, Baltimore, MD, U.S.A. aut Yu Kai Division of Epidemiology, Statistics and Prevention Research, National Institute of Child Health and Human Development, 20852, Bethesda, MD, U.S.A. aut Chiang Chin-Tsang Department of Statistics, Tunghai University, Taichung, Taiwan aut Annals of the Institute of Statistical Mathematics Kluwer Academic Publishers 52/3(2000-09-01), 519-543 0020-3157 52:3<519 2000 52 10463 https://doi.org/10.1023/A:1004125621021 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1023/A:1004125621021 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Wu Colin Department of Mathematical Sciences, The Johns Hopkins University, 21218, Baltimore, MD, U.S.A aut NATIONALLICENCE 700 1- Yu Kai Division of Epidemiology, Statistics and Prevention Research, National Institute of Child Health and Human Development, 20852, Bethesda, MD, U.S.A aut NATIONALLICENCE 700 1- Chiang Chin-Tsang Department of Statistics, Tunghai University, Taichung, Taiwan aut NATIONALLICENCE 773 0- Annals of the Institute of Statistical Mathematics Kluwer Academic Publishers 52/3(2000-09-01), 519-543 0020-3157 52:3<519 2000 52 10463 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer