标题： 一种回归方法解决两数据集问题 显示英文标题

标题： A regression approach to the two-dataset problem

摘要： 本文研究了两数据集问题，其中的数据是从两个可能不同的共享某些共同特征的总体中收集的。 当数据由两种不同类型的调查员收集或者来自两个不同来源时，此问题就会出现。 如果不利用关于数据收集过程的知识，我们可能会得出错误的结论。 为了解决这个问题，本文开发了统计回归模型，重点在于测量差异，并提出了两种预测误差，有助于评估潜在的数据收集过程。 因此，可以讨论预测方面预测器集合的异质性/相似性。 选择两个真实数据集来说明我们的方法。 显示英文摘要

摘要： This paper considers the two-dataset problem, where data are collected from two potentially different populations sharing common aspects. This problem arises when data are collected by two different types of researchers or from two different sources. We may reach invalid conclusions without using knowledge about the data collection process. To address this problem, this paper develops statistical regression models focusing on the difference in measurement and proposes two prediction errors that help to evaluate the underlying data collection process. As a consequence, it is possible to discuss the heterogeneity/similarity of the set of predictors in terms of prediction. Two real datasets are selected to illustrate our method.