Fan Li

Assistant Professor

Yale School of Public Health

United States

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Fan Li is an Assistant Professor at Yale University School of Public Health in the United States. His research focuses on causal inference methodologies, particularly in the context of cluster-randomized trials and mediation analysis. Recent publications highlight his work on model-robust standardization, bias correction in mediation analysis, and Bayesian approaches to treatment effects and causal estimation.

Fan Li

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Articles (30)

Correcting for bias due to mismeasured exposure in mediation analysis with a survival outcome

Identification and multiply robust estimation in causal mediation analysis across principal strata

Model‐Robust Standardization in Cluster‐Randomized Trials

A Bayesian nonparametric approach to mediation and spillover effects with multiple mediators in cluster-randomized trials

Selecting the optimal longitudinal cluster randomized design with a continuous outcome: Parallel-arm, crossover, or stepped-wedge

Using overlap weights to address extreme propensity scores in estimating restricted mean counterfactual survival times

Permutation tests for detecting treatment effect heterogeneity in cluster randomized trials

Assessing Mediation in Cross‐Sectional Stepped Wedge Cluster Randomized Trials

Revisiting representativeness

A Bayesian Approach to the G‐Formula via Iterative Conditional Regression

Information content of stepped wedge designs under the working independence assumption

Transporting randomized trial results to estimate counterfactual survival functions in target populations

Multiply robust estimation of principal causal effects with noncompliance and survival outcomes

Evaluating analytic models for individually randomized group treatment trials with complex clustering in nested and crossed designs

Correction: Sample Size Requirements to Test Subgroup-Specific Treatment Effects in Cluster-Randomized Trials

Demystifying estimands in cluster-randomised trials

Sample Size Requirements to Test Subgroup-Specific Treatment Effects in Cluster-Randomized Trials

Sample size and power calculation for testing treatment effect heterogeneity in cluster randomized crossover designs

Bayesian semi-parametric inference for clustered recurrent events with zero inflation and a terminal event

Optimal designs using generalized estimating equations in cluster randomized crossover and stepped wedge trials

Maintaining the validity of inference from linear mixed models in stepped-wedge cluster randomized trials under misspecified random-effects structures

Impact of Marital Stress on 1‐Year Health Outcomes Among Young Adults With Acute Myocardial Infarction

Maximin optimal cluster randomized designs for assessing treatment effect heterogeneity

Sample size requirements for testing treatment effect heterogeneity in cluster randomized trials with binary outcomes

Assessing exposure‐time treatment effect heterogeneity in stepped‐wedge cluster randomized trials

Generalizing the information content for stepped wedge designs: A marginal modeling approach

Sample size considerations for assessing treatment effect heterogeneity in randomized trials with heterogeneous intracluster correlations and variances

Estimating the causal effects of multiple intermittent treatments with application to COVID-19

A note on semiparametric efficient generalization of causal effects from randomized trials to target populations

Clustered restricted mean survival time regression

Collaborators (18)

Liangyuan Hu

Youngjoo Cho

Himanshu Joshi

Yongdong Ouyang

Elizabeth Stuart

Valeria Raparelli

Denise Esserman

Donna Spiegelman

Xinyuan Chen

Bryan Blette

Fan Li

Chao Cheng

Patrick J. Heagerty

Rachel Dreyer

Yuan Lu

Jiachen Cai

Lisa Wruck

Brennan Kahan

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