🤖 AI Summary
研究使用五折交叉拟合和机器学习方法（如随机森林和梯度提升机）估计响应倾向，以改进调查估计中的无应答调整问题。
📝 Abstract
This paper investigates whether five fold cross fitting improves nonresponse adjustment in survey estimation when flexible machine learning methods are used to estimate response propensities. We conduct a finite population Monte Carlo simulation with 90 experimental configurations and 2,000 replications per configuration, varying sample size, response rate, and the structure of the response mechanism. Logistic regression is used as a conventional parametric benchmark, while Random Forest and Gradient Boosting Machine are considered as flexible nonparametric models.