 The use of sampling weights in M‐quantile random‐effects regression: an application to Programme for International Student Assessment mathematics scoresFrancesco Schirripa Spagnolo, Nicola Salvati, Antonella D’Agostino and Ides Nicaise () Journal of the Royal Statistical Society Series C, 2020, vol. 69, issue 4, 991-1012 Abstract: 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. Date: 2020 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:bla:jorssc:v:69:y:2020:i:4:p:991-1012 Ordering information: This journal article can be ordered from Access Statistics for this article Journal of the Royal Statistical Society Series C is currently edited by R. Chandler and P. W. F. Smith More articles in Journal of the Royal Statistical Society Series C from Royal Statistical Society Contact information at EDIRC. |
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