抽样权在M分位数随机效应回归中的应用：对PISA数学成绩的应用
The use of sampling weights in the M-quantile random-effects regression: an application to PISA mathematics scores
摘要：
当研究人员的兴趣集中在条件分位数时，M分位数随机效应回归是一种有趣的建模多水平数据的方法。当数据是基于复杂的调查设计时，抽样权重必须纳入分析。提出了一种在M分位数随机效应回归中调整抽样权重的伪似然方法。拟议的方法适用于“2015年国际学生评估方案”调查的意大利样本，以研究在条件分布的各个分位数的数学性别差距。调查结果为“科学、技术、工程和数学”部门中女性比例低提供了可能的解释。
英文摘要：
M-quantile random-effects regression represents an interesting approach for modelling multilevel data when the interest of researchers is focused on the conditional quantiles. When data are based on complex survey designs, sampling weights have to be incorporate in the analysis. A pseudo-likelihood approach for accommodating sampling weights in the M-quantile random-effects regression is presented. The proposed methodology is applied to the Italian sample of the "Program for International Student Assessment 2015" survey in order to study the gender gap in mathematics at various quantiles of the conditional distribution. Findings offer a possible explanation of the low share of females in "Science, Technology, Engineering and Mathematics" sectors.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
