Variable selection in rank regression for analyzing longitudinal data

2016 ◽  
Vol 27 (8) ◽  
pp. 2447-2458 ◽  
Author(s):  
Liya Fu ◽  
You-Gan Wang
Keyword(s):  
Variable Selection ◽  
Longitudinal Data ◽  
Adaptive Lasso ◽  
New Method ◽  
Dispersion Function ◽  
Simulation Studies ◽  
Rank Regression ◽  
Oracle Properties ◽  
Effective Selection ◽  
Selection Of

In this paper, we consider variable selection in rank regression models for longitudinal data. To obtain both robustness and effective selection of important covariates, we propose incorporating shrinkage by adaptive lasso or SCAD in the Wilcoxon dispersion function and establishing the oracle properties of the new method. The new method can be conveniently implemented with the statistical software R. The performance of the proposed method is demonstrated via simulation studies. Finally, two datasets are analyzed for illustration. Some interesting findings are reported and discussed.

scholarly journals Joint Variable Selection of Mean-Covariance Model for Longitudinal Data

2013 ◽  
Vol 03 (01) ◽  
pp. 27-35 ◽  
Author(s):  
Dengke Xu ◽  
Zhongzhan Zhang ◽  
Liucang Wu
Keyword(s):  
Variable Selection ◽  
Longitudinal Data ◽  
Covariance Model ◽  
Joint Variable ◽  
Selection Of

New Statistical Methods Inspired by Data Collected from Alcohol and Substance Abuse Research

2018 ◽  
Author(s):  
Anne Buu ◽  
Runze Li
Keyword(s):  
Risk Factors ◽  
Substance Abuse ◽  
Longitudinal Data ◽  
Developmental Trajectories ◽  
Regression Splines ◽  
Simulation Studies ◽  
Process Data ◽  
Measurement Reactivity ◽  
Longitudinal Association ◽  
Highly Correlated

This chapter provides a nontechnical review of new statistical methodology for longitudinal data analysis that has been published in statistical journals in recent years. The methodology has applications in four important areas: (1) conducting variable selection among many highly correlated risk factors when the outcome measure is zero-inflated count; (2) characterizing developmental trajectories of symptomatology using regression splines; (3) modeling the longitudinal association between risk factors and substance use outcomes as time-varying effects; and (4) testing measurement reactivity and predictive validity using daily process data. The excellent statistical properties of the methods introduced have been supported by simulation studies. The applications in alcohol and substance abuse research have also been demonstrated by graphs on real longitudinal data.

Numerical simulation studies of Cs3Bi2I9 perovskite solar device with optimal selection of electron and hole transport layers

Optik ◽  
2021 ◽  
Vol 231 ◽  
pp. 166417 ◽  
Author(s):  
Md Tohidul Islam ◽  
Md Rafsun Jani ◽  
Kazi Md Shorowordi ◽  
Zameer Hoque ◽  
Ali Mucteba Gokcek ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Hole Transport ◽  
Optimal Selection ◽  
Simulation Studies ◽  
Hole Transport Layers ◽  
Selection Of

A New Method for Selecting the Best Design

2012 ◽  
Vol 20 (1) ◽  
pp. 11-17
Author(s):  
Mark E. Benden ◽  
Kristen Miller ◽  
Eric Wilke ◽  
Eduardo Ibarra
Keyword(s):  
Patient Outcomes ◽  
New Method ◽  
Driver Safety ◽  
Transport Vehicle ◽  
Medical Transport ◽  
Expert Ratings ◽  
Vehicle Seat ◽  
Improve Patient ◽  
Individual Expert ◽  
Selection Of

In this article the authors illustrate how individual expert ratings can be employed to prioritize specifications for use in forced rankings. Those rankings are then used to select a design with the best overall usability. The authors provide an example of this approach in the selection of a medical transport vehicle seat to produce a more ergonomic product that could improve patient outcomes and driver safety.

Stable variable selection of class-imbalanced data with precision-recall criterion

2017 ◽  
Vol 171 ◽  
pp. 241-250 ◽  
Author(s):  
Guang-Hui Fu ◽  
Feng Xu ◽  
Bing-Yang Zhang ◽  
Lun-Zhao Yi
Keyword(s):  
Variable Selection ◽  
Imbalanced Data ◽  
Stable Variable ◽  
Selection Of

CIVIL GOVERNOR M.M. OREUS IN THE SERVICE IN THE VYBORG (FINLAND) PROVINCE IN 1799–1804

2021 ◽  
Vol 10 (1) ◽  
pp. 39-46
Author(s):  
T.V. BOGDANOVA ◽  
Keyword(s):  
Russian Empire ◽  
Management Problem ◽  
Effective Mechanism ◽  
Important Condition ◽  
Emergency Situations ◽  
Effective Selection ◽  
History Of ◽  
The Government ◽  
The Russian Empire ◽  
Selection Of

The purpose of the article is to review the activities of the civil governor M.M. Oreus in the service in the Vyborg (Finland) province in 1799–1804. The guarantee of an effective mechanism of admin-istration creation as for over than 200-year period of the Russian Empire existence, as for modern conditions, it was and still is the effectiveness of the government policy on the ground. Based on this key task, the most important condition for its implementation at different stages of the development of the country was the effective selection of personnel for the post of a governor. It was the governor responsible for everything happened in his province, and the government expected him to under-stand the tasks assigned to him and take definite steps to solve them. The urgent management problem in these conditions was the strength of administrative resources capable of retaining their effective power in cases of emerging extraordinary situations, including which, will be discussed in this article. Emergency situations in the border areas occurred regularly and required the ob-servance of certain administrative traditions that influenced the success of the governor's initiatives in state tasks implementation. It will be all the more important to consider the history of the life and activities of one of the governors of the Finland (Vyborg) province, Maxim Maksimovich Oreus, who was at the head of this territory from December 14, 1799 to April 9, 1804.

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