Distributed Data Analysis Based on Single Index Model.

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Bibliographic Details
Title:	Distributed Data Analysis Based on Single Index Model.
Authors:	Jingcheng Xian¹ xianjc0602@163.com, Cheng Wang² chenw0808@163.com, Guangbao Guo³ ggb11111111@163.com
Source:	IAENG International Journal of Computer Science. Jul2025, Vol. 52 Issue 7, p2289-2294. 6p.
Subjects:	Distributed databases, Clinical trials
Abstract:	Amid randomized clinical trial data analysis, this article propose a distributed data analysis approach based on a single-index model that uniquely estimates the interaction between pre-processing covariates and treatment variables on the response variable. The method represents the interaction effects of the model via a set of therapy-specific adaptive link functions that act on a linear mixture of covariates (i.e., a single index) while satisfying the limitation that the expected value of the covariates is zero, while the primary effects of the covariates remain unspecified. By uniquely estimating the interaction effects between pre-processing covariates and treatment variables, we can optimize personalized treatment rules to improve clinical treatment outcomes. [ABSTRACT FROM AUTHOR]
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Database:	Engineering Source

Description
Abstract:	Amid randomized clinical trial data analysis, this article propose a distributed data analysis approach based on a single-index model that uniquely estimates the interaction between pre-processing covariates and treatment variables on the response variable. The method represents the interaction effects of the model via a set of therapy-specific adaptive link functions that act on a linear mixture of covariates (i.e., a single index) while satisfying the limitation that the expected value of the covariates is zero, while the primary effects of the covariates remain unspecified. By uniquely estimating the interaction effects between pre-processing covariates and treatment variables, we can optimize personalized treatment rules to improve clinical treatment outcomes. [ABSTRACT FROM AUTHOR]
ISSN:	1819656X