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Polygenic score prediction of psychopathology dimensions and diagnoses within and between families

Lin Y, Procopio F, Keser E, Kawakami K, Eley T, Rimfeld K, Malanchini M, Plomin R.   +7 more
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Bayesian composite quantile regression for linear mixed-effects models

Communications in Statistics - Theory and Methods, 2017
ABSTRACTLongitudinal data are commonly modeled with the normal mixed-effects models. Most modeling methods are based on traditional mean regression, which results in non robust estimation when suffering extreme values or outliers. Median regression is also not a best choice to estimation especially for non normal errors.
Yuzhu Tian, Heng Lian, Maozai Tian
openaire   +2 more sources

Double Penalized Quantile Regression for the Linear Mixed Effects Model

Journal of Systems Science and Complexity, 2020
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Li, Hanfang, Liu, Yuan, Luo, Youxi
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Linear mixed function‐on‐function regression models

Biometrics, 2014
SummaryWe develop a linear mixed regression model where both the response and the predictor are functions. Model parameters are estimated by maximizing the log likelihood via the ECME algorithm. The estimated variance parameters or covariance matrices are shown to be positive or positive definite at each iteration.
Wei Wang
openaire   +4 more sources