M‐quantile random‐effects regression represents an interesting approach for modelling multilevel data when the researcher is focused on conditional quantiles. When data are obtained from complex survey designs, sampling weights must be incorporated in the analysis. A robust pseudolikelihood approach for accommodating sampling weights in M‐quantile random‐effects regression is presented. In particular, the method is based on a robustification of the estimating equations. The methodology proposed is applied to the Italian sample of the Programme for International Student Assessment 2015 survey to study the gender gap in mathematics at various quantiles of the conditional distribution. The findings offer a possible explanation of the low proportion of women in science, technology, engineering and mathematics sectors.

中文翻译：

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抽样权重在M分位数随机效应回归中的应用：国际学生评估计划数学分数的应用

当研究人员专注于条件分位数时，M分位数的随机效应回归代表了一种有趣的方法来建模多级数据。从复杂的调查设计获得数据时，必须在分析中纳入抽样权重。用于在M中容纳采样权重的鲁棒伪似然方法提出了分位数的随机效应回归。特别地，该方法基于估计方程的鲁棒性。提议的方法应用于“ 2015年国际学生评估计划”调查的意大利样本，以研究在条件分布的各个分位数下数学上的性别差距。研究结果可能解释了科学，技术，工程和数学领域女性比例低下的情况。