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The British Journal of Mathematical and Statistical Psychology|June 17, 2025
Testing the validity of instrumental variables in just-identified linear non-Gaussian modelsWolfgang Wiedermann, Dexin ShiEducational and Psychological Measurement|May 22, 2026
Cumulant-Based Approaches for Testing the Assumption of Independent Errors in Non-Gaussian Parallel and Congeneric MeasuresWolfgang Wiedermann, Dexin ShiBehavior Research Methods|October 19, 2023
Detecting heterogeneity in the causal direction of dependence: A model-based recursive partitioning approachWolfgang Wiedermann, Bixi Zhang, Dexin ShiPsychological Methods|December 21, 2023
One step at a time: A statistical approach for distinguishing mediators, confounders, and colliders using direction dependence analysisDexin Shi, Amanda J Fairchild, Wolfgang WiedermannThe British Journal of Mathematical and Statistical Psychology|April 16, 2025
Distinguishing cause from effect in psychological research: An independence-based approach under linear non-Gaussian modelsDexin Shi, Bo Zhang, Wolfgang Wiedermann, et al.Multivariate Behavioral Research|April 13, 2019
Direction Dependence Analysis in the Presence of Confounders: Applications to Linear Mediation Models Using Observational DataWolfgang Wiedermann, James SebastianMultivariate Behavioral Research|September 24, 2019
Sensitivity Analysis and Extensions of Testing the Causal Direction of Dependence: A Rejoinder to Thoemmes (2019)Wolfgang Wiedermann, James SebastianBehavior Research Methods|April 18, 2018
Direction dependence analysis: A framework to test the direction of effects in linear models with an implementation in SPSSWolfgang Wiedermann, Xintong LiBehavior Research Methods|September 13, 2023
Covariate selection in causal learning under non-GaussianityBixi Zhang, Wolfgang WiedermannBehavior Research Methods|March 21, 2019
Confounder detection in linear mediation models: Performance of kernel-based tests of independenceWolfgang Wiedermann, Xintong LiPageof 11