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of 38
pro vyhledávání: '"Gao, Chenyin"'
This study introduces an innovative method for analyzing the impact of various interventions on customer churn, using the potential outcomes framework. We present a new causal model, the tensorized latent factor block hazard model, which incorporates
Externí odkaz:
http://arxiv.org/abs/2405.11377
Autor:
Faries, Douglas, Gao, Chenyin, Zhang, Xiang, Hazlett, Chad, Stamey, James, Yang, Shu, Ding, Peng, Shan, Mingyang, Sheffield, Kristin, Dreyer, Nancy
The assumption of no unmeasured confounders is a critical but unverifiable assumption required for causal inference yet quantitative sensitivity analyses to assess robustness of real-world evidence remains underutilized. The lack of use is likely in
Externí odkaz:
http://arxiv.org/abs/2309.07273
In recent years, real-world external controls (ECs) have grown in popularity as a tool to empower randomized placebo-controlled trials (RPCTs), particularly in rare diseases or cases where balanced randomization is unethical or impractical. However,
Externí odkaz:
http://arxiv.org/abs/2306.16642
Autor:
Gao, Chenyin, Yang, Shu
Multiple heterogeneous data sources are becoming increasingly available for statistical analyses in the era of big data. As an important example in finite-population inference, we develop a unified framework of the test-and-pool approach to general p
Externí odkaz:
http://arxiv.org/abs/2305.17801
Noise is ubiquitous during image acquisition. Sufficient denoising is often an important first step for image processing. In recent decades, deep neural networks (DNNs) have been widely used for image denoising. Most DNN-based image denoising methods
Externí odkaz:
http://arxiv.org/abs/2209.12715
Calibration weighting has been widely used to correct selection biases in non-probability sampling, missing data, and causal inference. The main idea is to calibrate the biased sample to the benchmark by adjusting the subject weights. However, hard c
Externí odkaz:
http://arxiv.org/abs/2206.01084
Nonresponse is a common problem in survey sampling. Appropriate treatment can be challenging, especially when dealing with detailed breakdowns of totals. Often, the nearest neighbor imputation method is used to handle such incomplete multinomial data
Externí odkaz:
http://arxiv.org/abs/2202.11276
Wildland fire smoke exposures are an increasing threat to public health, and thus there is a growing need for studying the effects of protective behaviors on reducing health outcomes. Emerging smartphone applications provide unprecedented opportuniti
Externí odkaz:
http://arxiv.org/abs/2005.12017
We propose a test-based elastic integrative analysis of the randomized trial and real-world data to estimate treatment effect heterogeneity with a vector of known effect modifiers. When the real-world data are not subject to bias, our approach combin
Externí odkaz:
http://arxiv.org/abs/2005.10579
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