发表论文 See CV for the full list

Yang, F., Lorch, S. A., and Small, D. S. (2014). ``Estimation of causal effects using instrumental variables with nonignorable missing covariates: Application to effect of type of delivery hospital on premature infants.'' Annals of Applied Statistics, Volume 8, Number 1, pp. 48-73.

Yang, F., Zubizarreta, J., Small, D. S., Lorch, S. A., and Rosenbaum, P. (2014). ``Dissonant conclusions when testing the validity of an instrumental variable." The American Statistician, Volume 68, Issue 4, pp. 253-263.

Yang, F. and Small, D. S. (2016). ``Using post-outcome measurement information in censoring-by-death problems." Journal of the Royal Statistical Society, Series B, Volume 78, Number 1, pp. 299-318.

Yang, F., Wang, J., the GTEx Consortium, Pierce, B. L, and Chen, L. S. (2017). ``Identifying cis-mediators for trans-eQTLs across many human tissues using genomic mediation analysis." Genome Research, Volume 27, pp. 1859-1871.

Yang, F. and Ding, P. (2018). ``Using survival information in truncation by death problems without the monotonicity assumption.'' Biometrics, Volume 74, Issue 4, pp. 1232-1239.

Gleason, K. J. #, Yang, F. #, Pierce, B. L., He, X., and Chen, L. S. (2020). ``Primo: integration of multiple GWAS and omics QTL summary statistics for elucidation of molecular mechanisms of trait-associated SNPs and detection of pleiotropy in complex traits.'' Genome Biology, Volume 21, 236.

Gleason, K. J., Yang, F. *, and Chen, L. S. * (2021). ``A robust two-sample transcriptome-wide Mendelian Randomization method integrating GWAS with multi-tissue eQTL summary statistics.'' Genetic Epidemiology, Volume 45, Issue 4, pp. 353-371.

Yang, F. *, Gleason, K. J., Wang, J., The GTEx Consortium, Duan, J., He, X, Pierce, B. L., and Chen, L. S. * (2021). ``CCmed: cross-condition mediation analysis for identifying replicable trans-associations mediated by cis-gene expression.'' Bioinformatics, Volume 37, Number 17, pp. 2513-2520.

Hong, G. #, Yang, F. #, Qin, X. (2022). ``Post-treatment confounding in causal mediation studies: A cutting-edge problem and a novel solution via sensitivity analysis.'' Biometrics, https://doi.org/10.1111/biom.13705.