2 citations · 2 across the 1 of their papers we have counts for
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Can Language Models Boost the Power of Randomized Experiments Without Statistical Bias?
Xinrui Ruan, Xinwei Ma, Yingfei Wang +2
Randomized controlled trials (RCTs) are widely adopted for causal inference, yet cost and sample-size constraints limit power. We introduce CALM (Causal Analysis leveraging Languag…
Covariate-Adjusted Response-Adaptive Design with Delayed Outcomes
Xinwei Ma, Jingshen Wang, Waverly Wei
Covariate-adjusted response-adaptive (CARA) designs have gained widespread adoption for their clear benefits in enhancing experimental efficiency and participant welfare. These des…
Mediation Analysis with Mendelian Randomization and Efficient Multiple GWAS Integration
Rita Qiuran Lyu, Chong Wu, Xinwei Ma +1
Mediation analysis is a powerful tool for studying causal pathways between exposure, mediator, and outcome variables of interest. While classical mediation analysis using observati…
Adaptive Experiments Toward Learning Treatment Effect Heterogeneity
Waverly Wei, Xinwei Ma, Jingshen Wang
Understanding treatment effect heterogeneity has become an increasingly popular task in various fields, as it helps design personalized advertisements in e-commerce or targeted tre…
Fair Adaptive Experiments
Waverly Wei, Xinwei Ma, Jingshen Wang
Randomized experiments have been the gold standard for assessing the effectiveness of a treatment or policy. The classical complete randomization approach assigns treatments based…