matching design
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BMJ Open ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. e052610
Author(s):  
Per Johansson ◽  
Paulina Jonéus ◽  
Sophie Langenskiöld

IntroductionThis paper presents a study protocol for a comparative effectiveness evaluation of abiraterone acetate against enzalutamide in clinical practice, two cancer drugs given to patients suffering from advanced prostate cancer.Method and analysisThe protocol designs a comparative-effectiveness analysis of abiraterone acetate against enzalutamide. With the substantial number of covariates a two-step procedure is suggested in choosing relevant covariates in the matching design. In the first step, an exploratory factor analysis reduces the dimension of a large set of continuous covariates to nine factors. In the second step, we reduce the dimension of the covariates, interactions and second order terms for the continuous covariates using propensity score estimation. The final design makes use of a genetic matching algorithm. The study protocol provides a detailed statistical analysis plan of the analysis sample derived from the matching design. The analysis will make use of linear regression and robust inference adjusted for multisignificance testing.DiscussionAs in a randomised experiment the focus is on the design of the assignment to treatment. This allows the publication of this preanalysis plan before having access to outcome data. This means that the p values will be correct if the maintained assumption of uncounfoundedness is valid. Given that is p-hacking is substantial problem in empirical research, this is a substantial strength of this study. However, while design yields, balance on the observed covariates one cannot discard the possibility that unobserved confounders are not balanced. For that reason, sensitivity tests for the maintained assumption of uncounfoundedness are presented.Ethics and disseminationThe study was approved by the Regional Ethical Review Board in Uppsala, Sweden (Dnr 2017/482). Results will be published in a peer-reviewed journal and distributed to relevant stakeholders in healthcare.


Author(s):  
Peng Li ◽  
Pei Li ◽  
Zeling Kuang ◽  
Lingyan Si ◽  
Menglin Huang
Keyword(s):  

2021 ◽  
Author(s):  
Yichen YAO ◽  
Yixin Su ◽  
Tianye Yu ◽  
Gexue Ren ◽  
Suyuan Yu

2021 ◽  
Author(s):  
Guang Li ◽  
Yuan Yao ◽  
Yadong Song ◽  
Guosheng Chen ◽  
Kang Chen

Abstract Hunting stability of high-speed train is an important dynamic performance for the design of bogie suspension parameters. An appropriate hunting stability margin is required for high-speed train. Besides, a remarkable ability to weaken the influence caused by the disturbance of bogie suspension parameters and wheel-rail contact parameters on hunting stability is also required. The matching design of bogie passive suspension parameters is an important means to ensure the train comprehensive stability. In this paper, the concept of robust hunting stability is proposed, and the indexes for suspension parameter robustness and wheel-rail contact equivalent conicity robustness are defined and chosen as the dynamic performance indexes for the bogie suspension parameters design. Design of Experiment (DOE) is used to search the suspension parameters to satisfy the defined robust hunting stability indexes. Vehicle linear stability analysis is performed based on a large number of combined random suspension parameters, and then the parameters satisfying the performance requirements are designed, from which the parameter matching rules are concluded based on the discrete statistical analysis. Using this method, the suspension parameters can be designed to satisfy the defined multiple vehicle dynamic performance indexes, instead of engineering experiences.


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