Results 41 to 50 of about 4,500 (154)
BMC Medical Research Methodology, 2019 Background The analysis of twin data presents a unique challenge. Second-born twins on average weigh less than first-born twins and have an elevated risk of perinatal mortality.
Muhammad Abu Shadeque Mullah +2 more
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Maximal Associated Regression: A Nonlinear Extension to Least Angle Regression
IEEE Access, 2021 This paper proposes Maximal Associated Regression (MAR), a novel algorithm that performs forward stage-wise regression by applying nonlinear transformations to fit predictor covariates.
Sanush K. Abeysekera +3 more
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Child growth curves: historical development, construction methodologies, and applications [PDF]
Linchuang erke zazhiGrowth curves are indispensable for monitoring children's growth in child health care and pediatrics. In our article, we traces growth curves ranging over 200 years, from the hand-drawn charts in the early 18th century to algorithmic modeling in modern ...
GAO Yufei, QIAN Naisi, YANG Zhiyu, JIN Shan, LU Huiping, WU Cheng, SONG Hualing, YU Huiting
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Factors Associated with Survival of Patients with Leukemia Using Penalized Splines and Comparing That with the Cox Proportional Hazards Model [PDF]
Journal of Mazandaran University of Medical Sciences, 2023 Background and purpose: Leukemia is one of the most common and deadly diseases which is an important health problem. The aim of this study was to evaluate the survival of patients with acute lymphoblastic leukemia (ALL) and acute myeloblastic leukemia ...
Afsaneh Fendereski +3 more
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Extensions of the Penalized Spline of Propensity Prediction Method of Imputation [PDF]
Biometrics, 2009 Summary Little and An (2004, Statistica Sinica 14, 949–968) proposed a penalized spline of propensity prediction (PSPP) method of imputation of missing values that yields robust model‐based inference under the missing at random assumption. The propensity score for a missing variable is estimated and a regression model is fitted that includes the ...
Zhang, Guangyu, Little, Roderick J. A.
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ModellingThis research aims to explore and compare several nonparametric regression techniques, including smoothing splines, natural cubic splines, B-splines, and penalized spline methods.
Autcha Araveeporn
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A Note on Penalized Spline Smoothing With Correlated Errors
Journal of the American Statistical Association, 2007 We investigate the behavior of data-driven smoothing parameters for penalized spline regression in the presence of correlated data. It has been shown for other smoothing methods that mean squared error minimizers, such as (generalized) cross-validation or the Akaike information criterion, are extremely sensitive to misspecifications of the correlation ...
Krivobokova, Tatyana, Kauermann, Goran
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Frontiers in EpidemiologyIntroductionThe Cox proportional hazards (PH) model is widely used in time-to-event research, but its validity depends on the PH assumption, which can be violated in child mortality studies where hazards vary with age. Piecewise exponential models (PEMs)
Peter Enesi Omaku +2 more
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, 2012 Regression spline is a useful tool in nonparametric regression. However, finding the optimal knot locations is a known difficult problem. In this article, we introduce the Non-concave Penalized Regression Spline. This proposal method not only produces smoothing spline with optimal convergence rate, but also can adaptively select optimal knots ...
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Comparative Analysis for Robust Penalized Spline Smoothing Methods [PDF]
Mathematical Problems in Engineering, 2014 Smoothing noisy data is commonly encountered in engineering domain, and currently robust penalized regression spline models are perceived to be the most promising methods for coping with this issue, due to their flexibilities in capturing the nonlinear trends in the data and effectively alleviating the disturbance from the outliers.
Bin Wang, Wenzhong Shi, Zelang Miao
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