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3 Jun 2024: Search. Confounder selection via iterative graph expansion. Date. 2023-09-17 12:00 AM — 12:00 AM. Pacific Causal Inference Conference. Location. Peking University, China. 2024. Powered by the Academic theme forCite.

3 Jun 2024: Search. Corpus. How infectious was COVID-19 when it first circulated in Wuhan?. This is given to A-level students. 2024. Powered by the Academic theme forCite.

3 Jun 2024: Search. Art Owen. Latest. Confounder adjustment in multiple hypothesis testing. 2024. Powered by the Academic theme forCite.

13 Jun 2024: Menu. College Complaints Procedure.

3 Jun 2024: Search. Reliable Inference for Precision Medicine. Abstract. Two central objectives of individualized treatment are precision and optimality. A third objective is robustness, and this talk aims to explore what could happen if we account for

3 Jun 2024: Search. Publications. Type. Uncategorized. Conference paper. Journal article. Preprint. Date. 2024. 2023. 2022. 2021. 2020. 2019. 2018. 2017. 2016. 2015. Tobias Freidling, Qingyuan Zhao, Zijun Gao (2024). Zixuan Wu, Ethan Lewis, Qingyuan Zhao,

3 Jun 2024: Search. Fisher. Discussion on (quasi-)randomization inference. The following is an email exchange with Hyunseung Kang on the nature of randomization inference. This was sparked by a couple of papers by David Freedman and David Lane: A Nonstochastic

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. Estimation and prediction in sparse and unbalanced tables. Qingyuan Zhao, Trevor Hastie, Daryl Pregibon. March 2017Abstract. When there is a multi-way table where each dimension has large number of levels, it is computationally intensive to

19 Jun 2024: No 6746. Wednesday 19 June 2024. Vol cliv No 36. pp. 699–703. Search. this issue. 2023-24. all issues. for. End of the Official Part of the ‘Reporter’. Correction:. 20 July 2024: The Notice on the Ballot timetable on the EJRA proposals has

13 Jun 2024: Then download and complete this form: Booking Request Form.

3 Jun 2024: Search. Discovering mechanistic heterogeneity using Mendelian randomization. Abstract. Mendelian Randomization (MR) is a popular method in epidemiology and genetics that uses genetic variation as instrumental variables for causal inference. Existing

3 Jun 2024: Search. Tom Palmer. Latest. Mendelian randomization. 2024. Powered by the Academic theme forCite.

3 Jun 2024: Search. Workflow. Migrating my website to Hugo Academic ox-hugo. Update <2021-05-30 Sun>: A template of this website is now available on GitHub. Being stuck at home during the pandemic, as miserable as it is, actually helps me to redesign my working

3 Jun 2024: Search. Randomization. Selective Randomization Inference for Adaptive Experiments. We apply ideas from post-selection inference to randomization tests for adaptive experiments. Discussion on (quasi-)randomization inference. The following is an email

3 Jun 2024: Search. Freedman. Discussion on (quasi-)randomization inference. The following is an email exchange with Hyunseung Kang on the nature of randomization inference. This was sparked by a couple of papers by David Freedman and David Lane: A

3 Jun 2024: Search. Phyllis Ju. Latest. BETS: The dangers of selection bias in early analyses of the coronavirus disease (COVID-19) pandemic. 2024. Powered by the Academic theme forCite.

3 Jun 2024: Search. Rajen Shah. Latest. BETS: The dangers of selection bias in early analyses of the coronavirus disease (COVID-19) pandemic. 2024. Powered by the Academic theme forCite.

3 Jun 2024: Search. Yang Jiang. Latest. ivmodel: An R package for inference and sensitivity analysis of instrumental variables models with one endogenous variable. 2024. Powered by the Academic theme forCite.

3 Jun 2024: Search. Using sparsity to overcome unmeasured confounding. 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 aspect—the