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3 Jun 2024: Search. Confounder Selection. We propose a systematic way to select confounders. Confounder selection: Objectives and approaches. We provide a unified review of various confounder selection criteria in the literature and the assumptions behind them.

3 Jun 2024: Search. William Sutherland. Latest. Quantifying and addressing the prevalence and bias of study designs in the environmental and social sciences. 2024. Powered by the Academic theme forCite.

3 Jun 2024: Search. Murat A Erdogdu. Latest. SEISMIC: A self-exciting point process model for predicting tweet popularity. 2024. Powered by the Academic theme forCite.

3 Jun 2024: Search. Randomization (project page). 2022-04-22. A related page isRelated. Publications. Selective Randomization Inference for Adaptive Experiments. We apply ideas from post-selection inference to randomization tests for adaptive experiments.

3 Jun 2024: Search. MR Data Challenge 2019. The role of lipoprotein subfractions in coronary artery disease. Abstract. This report entered the 2019 MR Data Challenge and contains reproducible R code for our analysis. Date. 2019-07-19. Event. Mendelian

3 Jun 2024: Search. Graphical diagnosis of confounding bias in instrumental variables analysis. Qingyuan Zhao, Dylan Small. May 2018Abstract. This research letter proposes a new diagnostic plot for IV analysis, so large bias ratios (compared to OLS estimator)

3 Jun 2024: Search. Improving the accuracy of two-sample summary data Mendelian randomization: moving beyond the NOME assumption. Jack Bowden, Fabiola Del Greco M, Cosetta Minelli, Debbie Lawlor, Qingyuan Zhao, Nuala Sheehan, John Thompson, George Davey Smith.

3 Jun 2024: Search. Randomized Experiment. A unified analysis of regression adjustment in randomized experiments. Regression adjustment is broadly applied in randomized trials under the premise that it usually improves the precision of a treatment effect

3 Jun 2024: Search. Using sparsity to overcome unmeasured confounding: Two examples. Abstract. Sparsity is often used to improve the interpretability of a statistical analysis and/or reduce the variance of a statistical estimator. This talk will explore another

3 Jun 2024: Search. Effect Modification. Selecting and ranking individualized treatment rules with unmeasured confounding. Optimal individualized treatment rules try to assign the best treatment to every individual, but it may be very sensitive to unmeasured

3 Jun 2024: Search. Mendelian randomization: Old and new insights. Abstract. Mendelian randomization (MR) is a method for causal inference that utilizes the natural experiment in genetic inheritance. The idea of MR can be traced back to the dawn of modern

3 Jun 2024: Search. Anton Rask Lundborg. Latest. Confounder selection: Objectives and approaches. 2024. Powered by the Academic theme forCite.

3 Jun 2024: Search. M. Maria Glymour. Latest. Mendelian randomization. 2024. Powered by the Academic theme forCite.

3 Jun 2024: Search. Marcus R. Munafò. Latest. Mendelian randomization. 2024. Powered by the Academic theme forCite.

3 Jun 2024: Search. Almost exact Mendelian randomization. Matt Tudball, George Davey Smith, Qingyuan Zhao. August 2022Type. 2024. Powered by the Academic theme forCite.

3 Jun 2024: Search. Falsification tests for instrumental variable designs with an application to tendency to operate. Luke Keele, Qingyuan Zhao, Rachel Kelz, Dylan Small. August 2018Abstract. We propose a falsification test for the IV assumptions using

3 Jun 2024: Search. Sensitivity analysis for inverse probability weighting estimators via the percentile bootstrap. Qingyuan Zhao, Dylan Small, Bhaswar Bhattarcharya. November 2017Abstract. Rosenbaum’s sensitivity analysis framework has several limitations: 1.

3 Jun 2024: Search. Two-sample instrumental variable analyses using heterogeneous samples. Qingyuan Zhao, Jingshu Wang, Wes Spiller, Jack Bowden, Dylan Small. August 2017Abstract. Many modern IV studies (especially Mendelian Randomization) are carried out with

3 Jun 2024: Search. On sensitivity value of pair-matched observational studies. February 2017Abstract. A crucial quantity in Rosenbaum’s sensitivity analysis is the ‘sensitivity value’, the amount of unmeasured confounding needed to alter the qualitative

3 Jun 2024: Search. Causal Inference with Observational Data: Common Designs and Statistical Methods (2023). Course description. Observational studies are non-interventional empirical investigations of causal effects and are playing an increasingly vital role