Zobrazeno 1 - 10
of 1 169
pro vyhledávání: '"Zhou, Xiao‐hua"'
Regression discontinuity designs are widely used when treatment assignment is determined by whether a running variable exceeds a predefined threshold. However, most research focuses on estimating local causal effects at the threshold, leaving the cha
Externí odkaz:
http://arxiv.org/abs/2412.20840
In clinical practice, multiple biomarkers are often measured on the same subject for disease diagnosis, and combining them can improve diagnostic accuracy. Existing studies typically combine multiple biomarkers by maximizing the Area Under the ROC Cu
Externí odkaz:
http://arxiv.org/abs/2412.17471
Ratings of a user to most items in recommender systems are usually missing not at random (MNAR), largely because users are free to choose which items to rate. To achieve unbiased learning of the prediction model under MNAR data, three typical solutio
Externí odkaz:
http://arxiv.org/abs/2406.17182
When evaluating the effectiveness of a drug, a Randomized Controlled Trial (RCT) is often considered the gold standard due to its perfect randomization. While RCT assures strong internal validity, its restricted external validity poses challenges in
Externí odkaz:
http://arxiv.org/abs/2406.04107
Publication bias (PB) poses a significant threat to meta-analysis, as studies yielding notable results are more likely to be published in scientific journals. Sensitivity analysis provides a flexible method to address PB and to examine the impact of
Externí odkaz:
http://arxiv.org/abs/2406.04095
Instruction Fine-Tuning enhances pre-trained language models from basic next-word prediction to complex instruction-following. However, existing One-off Instruction Fine-Tuning (One-off IFT) method, applied on a diverse instruction, may not effective
Externí odkaz:
http://arxiv.org/abs/2406.04371
Publication bias (PB) is one of the serious issues in meta-analysis. Many existing methods dealing with PB are based on the normal-normal (NN) random-effects model assuming normal models in both the within-study and the between-study levels. For rare
Externí odkaz:
http://arxiv.org/abs/2405.03603
Autor:
Hu, Taojun, Zhou, Xiao-Hua
Natural Language Processing (NLP) is witnessing a remarkable breakthrough driven by the success of Large Language Models (LLMs). LLMs have gained significant attention across academia and industry for their versatile applications in text generation,
Externí odkaz:
http://arxiv.org/abs/2404.09135
In randomized controlled trials (RCT) with time-to-event outcomes, intercurrent events occur as semi-competing/competing events, and they could affect the hazard of outcomes or render outcomes ill-defined. Although five strategies have been proposed
Externí odkaz:
http://arxiv.org/abs/2401.14684
Semi-competing risks refer to the phenomenon that the terminal event (such as death) can censor the non-terminal event (such as disease progression) but not vice versa. The treatment effect on the terminal event can be delivered either directly follo
Externí odkaz:
http://arxiv.org/abs/2309.01721