我们的网站为什么显示成这样？

可能因为您的浏览器不支持样式，您可以更新您的浏览器到最新版本，以获取对此功能的支持，访问下面的网站，获取关于浏览器的信息：

|本期目录/Table of Contents|

 基于正则化的探索性中介分析:原理与应用(PDF)

《心理学探新》[ISSN:1003-5184/CN:36-1228/B]

期数:
 2022年03期
页码:
 261-268
栏目:
 心理统计与测量
出版日期:
 2022-06-20

文章信息/Info

Title:
 The Principle and Application of Exploratory Mediation Analysis via Regularization
文章编号:
1003-5184(2022)03-0261-08
作者:
 邓雅婷; 张沥今; 潘俊豪
 (中山大学心理学系,广州 510006)
Author(s):
 Deng Yating Zhang Lijin Pan Junhao
 (Department of Psychology,Sun Yat-sen University,Guangzhou 510006)
关键词:
 中介效应;  探索性中介分析;  正则化;  Lasso
Keywords:
 mediation;  exploratory mediation analysis;  regularization;  Lasso
分类号:
 B841.2
DOI:
 -
文献标识码:
 A
摘要:
 探索性中介分析被定义为从变量集合中筛选潜在中介变量的方法,该方法能在缺乏理论基础的情况下帮助研究者从数据中挖掘潜在中介机制,提供模型构建上的指导。本文介绍了一种基于正则化的探索性中介分析方法XMed(exploratory mediation analysis via regularization)。相比于传统探索性中介分析方法,XMed具有检验力更高、所需样本量更小、能高效地处理高维数据等优点,在认知神经科学、临床心理学等心理学领域有较大的应用潜力。本文主要介绍XMed的原理和实现过程,并通过实例分析展示该方法的应用。
Abstract:
 Mediation analysis is common in social science.Exploratory mediation analysis is defined as a series of data-driven methods for identifying potential mediators from a set of variables.It offers insights into the potential mediation process from data and provides guidance on model building.This article introduces the approach of exploratory mediation analysis via regularization(XMed).Compared to conventional exploratory mediation analysis approaches,XMed has higher sensitivity and needs less sample size.Moreover,it can handle high-dimensional data efficiently,which endows XMed a great potential for application in fields including cognitive neuroscience and clinical psychology.This article focuses on the principle and implementation of XMed.An empirical analysis is included to demonstrate the application of XMed.

参考文献/References

 方杰,温忠麟,张敏强.(2014).基于结构方程模型的多重中介效应分析. 心理科学,37(3),735-741.
柳士顺,凌文辁.(2009).多重中介模型及其应用.心理科学,32(2),433-435+407.
温忠麟,侯杰泰,张雷.(2005).调节效应与中介效应的比较和应用.心理学报,37(2),268-274.
朱廷劭.(2016).大数据时代的心理学研究及应用.科学出版社.
张沥今,魏夏琰,陆嘉琦,潘俊豪.(2020).Lasso回归:从解释到预测.心理科学进展,28(10),1777-1791.
Akaike,H.(1998).Information theory and an extension of the maximum likelihood principle.In E.Parzen,K.Tanabe,& G.Kitagawa(Eds.),Selected papers of hirotugu akaike(pp.199-213).Springer New York.
Ammerman,B.A.,Serang,S.,Jacobucci,R.,Burke,T.A.,Alloy,L.B.,& McCloskey,M.S.(2018).Exploratory analysis of mediators of the relationship between childhood maltreatment and suicidal behavior.Journal of Adolescence,69,103-112.
Babyak,M.A.(2004).What you see may not be what you get:A brief,nontechnical introduction to overfitting in regression-type models.Psychosomatic Medicine,66(3),411-421.
Beck,A.T.(1993).Cognitive therapy of depression:A personal reflection.Aberdeen,Scotland:Scottish Cultural Press.
Casella,G.,Ghosh,M.,Gill,J.,& Kyung,M.(2010).Penalized regression,standard errors,and Bayesian lassos.Bayesian Analysis,5(2),369-411.
Cohen,J.,Cohen,P.,West,S.G.,& Aiken,L.S.(2003).Applied multiple regression/correlation analysis for the behavioral sciences.Routledge.
Derksen,S.,& Keselman,H.J.(1992).Backward,forward and stepwise automated subset selection algorithms:Frequency of obtaining authentic and noise variables.British Journal of Mathematical and Statistical Psychology,45(2),265-282.
Guyon,I.,& Elisseeff,A.(2003).An introduction to variable and feature selection.The Journal of Machine Learning Research,3,1157-1182.
Hastie,T.,Tibshirani,R.,& Friedman,J.(2009).The elements of statistical learning:Data mining,inference,and prediction.Springer Science & Business Media.
Hayes,A.F.(2017).Introduction to mediation,moderation,and conditional process analysis:A regression-based approach.Guilford Publications.
Jacobucci,R.(2017).Regsem:Regularized structural equation modeling.ArXiv:1703.08489 [Stat].http://arxiv.org/abs/1703.08489
Jacobucci,R.,Grimm,K.J.,& McArdle,J.J.(2016).Regularized structural equation modeling.Structural Equation Modeling:A Multidisciplinary Journal,23(4),555-566.
Judd,C.M.,& Kenny,D.A.(1981).Process analysis:Estimating mediation in treatment evaluations.Evaluation Review,5(5),602-619.
Lieberman,M.D.,& Cunningham,W.A.(2009).Type I and Type II error concerns in fMRI research:Re-balancing the scale.Social Cognitive and Affective Neuroscience,4(4),423-428.
Locke,E.A.(2007).The case for inductive theory building.Journal of Management,33(6),867-890.
MacKinnon,D.P.(2008).Introduction to statistical mediation analysis.Taylor & Francis Group/Lawrence Erlbaum Associates.
MacKinnon,D.P.,Warsi,G.,& Dwyer,J.H.(1995).A simulation study of mediated effect measures.Multivariate Behavioral Research,30(1),41-62.
McNeish,D.M.(2015).Using lasso for predictor selection and to assuage overfitting:A method long overlooked in behavioral sciences.Multivariate Behavioral Research,50(5),471-484.
Meinshausen,N.(2007).Relaxed lasso.Computational Statistics & Data Analysis,52(1),374-393.
Muthén,L.K.,& Muthén,B.O.(2017).Mplus user's guide(version 8).Muthén & Muthén.
Pieters,R.(2017).Mediation analysis:Inferring causal processes in marketing from experiments.In P.S.Leeflang,J.E.Wieringa,T.H.Bijmolt,& K.H.Pauwels(Eds.),Advanced methods for modeling markets(pp.235-263).Springer.
Preacher,K.J.,& Hayes,A.F.(2008).Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models.Behavior Research Methods,40(3),879-891.
Rosseel,Y.(2012).Lavaan:An R package for structural equation modeling and more.Journal of Statistical Software,48(2),1-36.
Rosseel,Y.(2020).Small sample solutions for structural equation modeling.In R.Vande Schoot & M.Miocevic'(Eds.),Small sample size solutions(pp.226-238).Routledge.
Rucker,D.D.,Preacher,K.J.,Tormala,Z.L.,& Petty,R.E.(2011).Mediation analysis in social psychology:Current practices and new recommendations.Social and Personality Psychology Compass,5(6),359-371.
Schwarz,G.(1978).Estimating the dimension of a model.Annals of Statistics,6(2),461-464.
Serang,S.,& Jacobucci,R.(2020).Exploratory mediation analysis of dichotomous outcomes via regularization.Multivariate Behavioral Research,55(1),69-86.
Serang,S.,Jacobucci,R.,Brimhall,K.C.,& Grimm,K.J.(2017).Exploratory mediation analysis via regularization.Structural Equation Modeling:A Multidisciplinary Journal,24(5),733-744.
Stone,M.(1974).Cross-validatory choice and assessment of statistical predictions.Journal of the Royal Statistical Society:Series B(Methodological),36(2),111-133.
Tibshirani,R.(1996).Regression shrinkage and selection via the lasso.Journal of the Royal Statistical Society:Series B(Methodological),58(1),267-288.
Tourangeau,K.,Nord,C.,Lê,T.,Sorongon,A.G.,Hagedorn,M.C.,Daly,P.,& Najarian,M.(2015).Early childhood longitudinal study,kindergarten class of 2010-11(ECLS-K:2011).User's manual for the ECLS-K:2011 kindergarten data file and electronic codebook,public version(NCES 2015-074).U.S.Department of Education.National Center for Education Statistics.
vanErp,S.,Oberski,D.L.,& Mulder,J.(2019).Shrinkage priors for Bayesian penalized regression.Journal of Mathematical Psychology,89,31-50.
vanKesteren,E.-J.,& Oberski,D.L.(2019).Exploratory mediation analysis with many potential mediators.Structural Equation Modeling:A Multidisciplinary Journal,26(5),710-723.
Wood,R.E.,Goodman,J.S.,Beckmann,N.,& Cook,A.(2008).Mediation testing in management research:A review and proposals.Organizational Research Methods,11(2),270-295.
Yarkoni,T.,& Westfall,J.(2017).Choosing prediction over explanation in psychology:Lessons from machine learning.Perspectives on Psychological Science:A Journal of the Association for Psychological Science,12(6),1100-1122.

备注/Memo

备注/Memo:
 基金项目:国家自然科学基金项目(31871128),广东省自然科学基金项目(2022A1515010367)。
通讯作者:潘俊豪,E-mail:panjunh@mail.sysu.edu.cn。
更新日期/Last Update:  2022-11-20