4 papers · 1 filter
Debiased Machine Learning for Count Data: a Partially Linear Poisson Model Based on Neural Networks
Ningkun Zhou, Bryan E. Shepherd, Qingyan Xiang
We develop a novel debiased machine learning (DML) estimator to analyze count data, which are common in clinical or biomedical studies. Specifically, we estimate the effect of a bi…
Nonlinear trajectories of lung function recovery in patients with pulmonary disease: empirical evaluation of longitudinal modeling approaches
Zongyue Teng, Ningkun Zhou, Xinyu Zhang +2
Introduction: Longitudinal lung function recovery after pulmonary disease commonly follows nonlinear trajectories, and failure to adequately model these trajectories can lead to bi…
Analytical and Bootstrap Confidence Intervals for Double Machine Learning: Simulation Studies and an Application to Rural-Urban Differences in Obesity Prevalence
Haozheng Xu, Siyuan Ma, Qingyan Xiang
Double Machine Learning (DML) is a popular approach for treatment effect estimation in various settings, which allows a wide range of flexible machine learning methods to be used f…
Using large language models for sensitivity analysis in causal inference: case studies on Cornfield inequality and E-value
Qingyan Xiang, Jiahao Zhang, Bojian Feng
Sensitivity analysis methods such as the Cornfield inequality and the E-value were developed to assess the robustness of observed associations against unmeasured confounding -- a m…