Testing mediation effects using logic of Boolean matrices
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Meinshausen, Nicolai & Meier, Lukas & Bühlmann, Peter, 2009. "p-Values for High-Dimensional Regression," Journal of the American Statistical Association, American Statistical Association, vol. 104(488), pages 1671-1681.
- Shi, Chengchun & Song, Rui & Chen, Zhao & Li, Runze, 2019. "Linear hypothesis testing for high dimensional generalized linear models," LSE Research Online Documents on Economics 102108, London School of Economics and Political Science, LSE Library.
- Rubin Daniel & Dudoit Sandrine & van der Laan Mark, 2006. "A Method to Increase the Power of Multiple Testing Procedures Through Sample Splitting," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 5(1), pages 1-20, August.
- Victor Chernozhukov & Denis Chetverikov & Kengo Kato, 2012.
"Gaussian approximations and multiplier bootstrap for maxima of sums of high-dimensional random vectors,"
Papers
1212.6906, arXiv.org, revised Jan 2018.
- Victor Chernozhukov & Denis Chetverikov & Kengo Kato, 2013. "Gaussian approximations and multiplier bootstrap for maxima of sums of high-dimensional random vectors," CeMMAP working papers 76/13, Institute for Fiscal Studies.
- Victor Chernozhukov & Denis Chetverikov & Kengo Kato, 2013. "Gaussian approximations and multiplier bootstrap for maxima of sums of high-dimensional random vectors," CeMMAP working papers CWP76/13, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Yiping Yuan & Xiaotong Shen & Wei Pan & Zizhuo Wang, 2019. "Constrained likelihood for reconstructing a directed acyclic Gaussian graph," Biometrika, Biometrika Trust, vol. 106(1), pages 109-125.
- Fan J. & Li R., 2001. "Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1348-1360, December.
- Yen-Tsung Huang & Wen-Chi Pan, 2016. "Hypothesis test of mediation effect in causal mediation model with high-dimensional continuous mediators," Biometrics, The International Biometric Society, vol. 72(2), pages 402-413, June.
- Shi, Chengchun & Fan, Ailin & Song, Rui & Lu, Wenbin, 2018. "High-dimensional A-learning for optimal dynamic treatment regimes," LSE Research Online Documents on Economics 102113, London School of Economics and Political Science, LSE Library.
- Yunzhang Zhu & Xiaotong Shen & Wei Pan, 2020. "On High-Dimensional Constrained Maximum Likelihood Inference," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 115(529), pages 217-230, January.
- Shi, Chengchun & Song, Rui & Lu, Wenbin & Li, Runzi, 2020. "Statistical inference for high-dimensional models via recursive online-score estimation," LSE Research Online Documents on Economics 103043, London School of Economics and Political Science, LSE Library.
- Jianqing Fan & Jinchi Lv, 2008. "Sure independence screening for ultrahigh dimensional feature space," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(5), pages 849-911, November.
- J. Peters & P. Bühlmann, 2014. "Identifiability of Gaussian structural equation models with equal error variances," Biometrika, Biometrika Trust, vol. 101(1), pages 219-228.
- Cun-Hui Zhang & Stephanie S. Zhang, 2014. "Confidence intervals for low dimensional parameters in high dimensional linear models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 76(1), pages 217-242, January.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Li, Lexin & Shi, Chengchun & Guo, Tengfei & Jagust, William J., 2022. "Sequential pathway inference for multimodal neuroimaging analysis," LSE Research Online Documents on Economics 111904, London School of Economics and Political Science, LSE Library.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Christian Hansen & Kengo Kato, 2018.
"High-dimensional econometrics and regularized GMM,"
CeMMAP working papers
CWP35/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Christian Hansen & Kengo Kato, 2018. "High-Dimensional Econometrics and Regularized GMM," Papers 1806.01888, arXiv.org, revised Jun 2018.
- Xue Wu & Chixiang Chen & Zheng Li & Lijun Zhang & Vernon M. Chinchilli & Ming Wang, 2024. "A three-stage approach to identify biomarker signatures for cancer genetic data with survival endpoints," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 33(3), pages 863-883, July.
- Li, Lexin & Shi, Chengchun & Guo, Tengfei & Jagust, William J., 2022. "Sequential pathway inference for multimodal neuroimaging analysis," LSE Research Online Documents on Economics 111904, London School of Economics and Political Science, LSE Library.
- Guo, Xu & Li, Runze & Liu, Jingyuan & Zeng, Mudong, 2023. "Statistical inference for linear mediation models with high-dimensional mediators and application to studying stock reaction to COVID-19 pandemic," Journal of Econometrics, Elsevier, vol. 235(1), pages 166-179.
- Peter Bühlmann & Jacopo Mandozzi, 2014. "High-dimensional variable screening and bias in subsequent inference, with an empirical comparison," Computational Statistics, Springer, vol. 29(3), pages 407-430, June.
- Hansen, Christian & Liao, Yuan, 2019.
"The Factor-Lasso And K-Step Bootstrap Approach For Inference In High-Dimensional Economic Applications,"
Econometric Theory, Cambridge University Press, vol. 35(3), pages 465-509, June.
- Christian Hansen & Yuan Liao, 2016. "The Factor-Lasso and K-Step Bootstrap Approach for Inference in High-Dimensional Economic Applications," Papers 1611.09420, arXiv.org, revised Dec 2016.
- Christian Hansen & Yuan Liao, 2016. "The Factor-Lasso and K-Step Bootstrap Approach for Inference in High-Dimensional Economic Applications," Departmental Working Papers 201610, Rutgers University, Department of Economics.
- Hansen, Christian & Liao, Yuan, 2016. "The Factor-Lasso and K-Step Bootstrap Approach for Inference in High-Dimensional Economic Applications," MPRA Paper 75313, University Library of Munich, Germany.
- Ian W. McKeague & Min Qian, 2015. "An Adaptive Resampling Test for Detecting the Presence of Significant Predictors," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1422-1433, December.
- Jingxuan Luo & Lili Yue & Gaorong Li, 2023. "Overview of High-Dimensional Measurement Error Regression Models," Mathematics, MDPI, vol. 11(14), pages 1-22, July.
- Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015.
"Valid Post-Selection and Post-Regularization Inference: An Elementary, General Approach,"
Annual Review of Economics, Annual Reviews, vol. 7(1), pages 649-688, August.
- Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Valid Post-Selection and Post-Regularization Inference: An Elementary, General Approach," Papers 1501.03430, arXiv.org, revised Aug 2015.
- Victor Chernozhukov & Christian Hansen & Martin Spindler, 2016. "Valid post-selection and post-regularization inference: An elementary, general approach," CeMMAP working papers 36/16, Institute for Fiscal Studies.
- Victor Chernozhukov & Christian Hansen & Martin Spindler, 2016. "Valid post-selection and post-regularization inference: An elementary, general approach," CeMMAP working papers CWP36/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Guo, Xu & Li, Runze & Liu, Jingyuan & Zeng, Mudong, 2024. "Reprint: Statistical inference for linear mediation models with high-dimensional mediators and application to studying stock reaction to COVID-19 pandemic," Journal of Econometrics, Elsevier, vol. 239(2).
- Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015.
"Post-Selection and Post-Regularization Inference in Linear Models with Many Controls and Instruments,"
American Economic Review, American Economic Association, vol. 105(5), pages 486-490, May.
- Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Post-selection and post-regularization inference in linear models with many controls and instruments," CeMMAP working papers 02/15, Institute for Fiscal Studies.
- Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Post-Selection and Post-Regularization Inference in Linear Models with Many Controls and Instruments," Papers 1501.03185, arXiv.org.
- Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Post-selection and post-regularization inference in linear models with many controls and instruments," CeMMAP working papers CWP02/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Kock, Anders Bredahl, 2016. "Oracle inequalities, variable selection and uniform inference in high-dimensional correlated random effects panel data models," Journal of Econometrics, Elsevier, vol. 195(1), pages 71-85.
- Haixiang Zhang & Jun Chen & Zhigang Li & Lei Liu, 2021. "Testing for Mediation Effect with Application to Human Microbiome Data," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 13(2), pages 313-328, July.
- Sardy, Sylvain & Diaz-Rodriguez, Jairo & Giacobino, Caroline, 2022. "Thresholding tests based on affine LASSO to achieve non-asymptotic nominal level and high power under sparse and dense alternatives in high dimension," Computational Statistics & Data Analysis, Elsevier, vol. 173(C).
- Qing Zhou & Seunghyun Min, 2017. "Uncertainty quantification under group sparsity," Biometrika, Biometrika Trust, vol. 104(3), pages 613-632.
- Gabriel E Hoffman & Benjamin A Logsdon & Jason G Mezey, 2013. "PUMA: A Unified Framework for Penalized Multiple Regression Analysis of GWAS Data," PLOS Computational Biology, Public Library of Science, vol. 9(6), pages 1-19, June.
- Huang, Yuan & Li, Changcheng & Li, Runze & Yang, Songshan, 2022. "An overview of tests on high-dimensional means," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
- Xiaoyi Zhu & Yuhong Yang, 2015. "Variable selection after screening: with or without data splitting?," Computational Statistics, Springer, vol. 30(1), pages 191-203, March.
- DiCiccio, Cyrus J. & DiCiccio, Thomas J. & Romano, Joseph P., 2020. "Exact tests via multiple data splitting," Statistics & Probability Letters, Elsevier, vol. 166(C).
- Lan, Wei & Zhong, Ping-Shou & Li, Runze & Wang, Hansheng & Tsai, Chih-Ling, 2016. "Testing a single regression coefficient in high dimensional linear models," Journal of Econometrics, Elsevier, vol. 195(1), pages 154-168.
More about this item
Keywords
Boolean matrix; Directed acyclic graph; Gaussian graphical model; High-dimensional inference; Mediation analysis; Neuroimaging analysis;All these keywords.
JEL classification:
- C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
NEP fields
This paper has been announced in the following NEP Reports:- NEP-ECM-2022-05-02 (Econometrics)
- NEP-ORE-2022-05-02 (Operations Research)
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ehl:lserod:108881. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: LSERO Manager (email available below). General contact details of provider: https://edirc.repec.org/data/lsepsuk.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.