Jiannan Lu
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Continuous monitoring of A/B tests without pain: Optional stopping in Bayesian testing
A Deng, J Lu, S Chen
2016 IEEE International Conference on Data Science and Advanced Analyticsá…, 2016
Principal stratification analysis using principal scores
P Ding, J Lu
Journal of the Royal Statistical Society: Series B (Statistical Methodologyá…, 2016
Trustworthy analysis of online A/B tests: Pitfalls, challenges and solutions
A Deng, J Lu, J Litz
The Tenth ACM International Conference on Web Search and Data Mining (WSDMá…, 2017
Covariate adjustment in randomization-based causal inference for 2ᴷ factorial designs
J Lu
Statistics & Probability Letters 119, 11-20, 2016
On randomization-based and regression-based inferences for 2ᴷ factorial designs
J Lu
Statistics and Probability Letters 112, 72-78, 2016
Treatment effects on ordinal outcomes: Causal estimands and sharp bounds
J Lu, P Ding, T Dasgupta
Journal of Educational and Behavioral Statistics 43 (5), 540-567, 2018
Concise summarization of heterogeneous treatment effect using total variation regularized regression
A Deng, P Zhang, S Chen, DW Kim, J Lu
arXiv preprint arXiv:1610.03917, 2016
A note on type S/M errors in hypothesis testing
J Lu, Y Qiu, A Deng
British Journal of Mathematical and Statistical Psychology 72 (1), 1-17, 2018
Applying the Delta method in metric analytics: A practical guide with novel ideas
A Deng, U Knoblich, J Lu
Proceedings of the 24th ACM SIGKDD International Conference on Knowledgeá…, 2018
Demystifying the bias from selective inference: A revisit to Dawid's treatment selection problem
J Lu, A Deng
Statistics & Probability Letters 118, 8-15, 2016
Construction of alternative hypotheses for randomization tests with ordinal outcomes
J Lu, P Ding, T Dasgupta
Statistics & Probability Letters 107, 348-355, 2015
On randomization-based causal inference for matched-pair factorial designs
J Lu, A Deng
Statistics & Probability Letters 125, 99-103, 2017
On the partial identification of a new causal measure for ordinal outcomes
J Lu
Statistics & Probability Letters 137, 1-8, 2018
Sharpening randomization-based causal inference for 2▓ factorial designs with binary outcomes
J Lu
Statistical Methods in Medical Research 28 (4), 1064-1078, 2017
On Causal Inference for Ordinal Outcomes
J Lu
Harvard University, 2015
On Post-Selection Inference in A/B Tests
A Deng, Y Li, J Lu
arXiv preprint arXiv:1910.03788, 2019
Sharp bounds on the relative treatment effect for ordinal outcomes
J Lu, Y Zhang, P Ding
Biometrics 76 (2), 664-669, 2019
Improved Neymanian analysis for 2ᴷ factorial designs with binary outcomes
J Lu
Statistica Neerlandica 73 (4), 514-523, 2019
On heavy-user bias in A/B testing
Y Wang, S Gupta, J Lu, A Mahmoudzadeh, S Liu
Proceedings of the 28th ACM International Conference on Information andá…, 2019
On finite-population Bayesian inferences for 2ᴷ factorial designs with binary outcomes
J Lu
Journal of Statistical Computation and Simulation 89 (5), 927-945, 2019
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