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BMC Medical Research Methodology|February 10, 2024
A data-adaptive method for investigating effect heterogeneity with high-dimensional covariates in Mendelian randomizationHaodong Tian, Brian D M Tom, Stephen BurgessInternational Journal of Epidemiology|January 20, 2023
Estimation of time-varying causal effects with multivariable Mendelian randomization: some cautionary notesHaodong Tian, Stephen BurgessBiostatistics (Oxford, England)|November 30, 2025
Stratification-based instrumental variable analysis framework for nonlinear effect analysisHaodong Tian, Ashish Patel, Stephen BurgessStatistics in Medicine|October 7, 2024
Estimating Time-Varying Exposure Effects Through Continuous-Time Modelling in Mendelian RandomizationHaodong Tian, Ashish Patel, Stephen BurgessPlos Genetics|June 30, 2023
Relaxing parametric assumptions for non-linear Mendelian randomization using a doubly-ranked stratification methodHaodong Tian, Amy M Mason, Cunhao Liu, et al.HGG Advances|January 18, 2026
Variant selection to maximize variance explained in cis-Mendelian randomizationAng Zhou, Ville Karhunen, Haodong Tian, et al.Statistics in Medicine|June 5, 2013
Identifying the odds ratio estimated by a two-stage instrumental variable analysis with a logistic regression modelStephen Burgess, International Journal of Epidemiology|March 11, 2014
Sample size and power calculations in Mendelian randomization with a single instrumental variable and a binary outcomeStephen BurgessHuman Heredity|August 31, 2023
Violation of the Constant Genetic Effect Assumption Can Result in Biased Estimates for Non-Linear Mendelian RandomizationStephen BurgessStatistics in Medicine|February 4, 2026
A Tutorial on Optimal Dynamic Treatment RegimesChunyu Wang, Brian D M TomPageof 47