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Accounting for sex and gender characteristics is a complex, structural challenge in social science research. While other methodology papers consider issues surrounding appropriate measurement, we consider how gender and sex impact adjustments for non-response patterns in sampling and survey estimates. We consider the problem of survey adjustment arising from the recent push toward measuring sex or gender as a non-binary construct. This is challenging not only in that response categories differ between sex and gender measurement, but also in that both of these attributes are potentially multidimensional. In this manuscript we reflect on similarities to measuring race/ethnicity before considering the ethical and statistical implications of the options available to us. We do not conclude with a single best recommendation but rather an awareness of the complexity of the issues surrounding this challenge and the benefits and weaknesses of different approaches.
Strikingly few Nobel laureates within medicine, natural and social sciences are women. Although it is obvious that there are fewer women researchers within these fields, does this gender ratio still fully account for the low number of female Nobel la
The sex ratio at birth (SRB) in India has been reported imbalanced since the 1970s. Previous studies have shown a great variation in the SRB across geographic locations in India till 2016. As one of the most populous countries and in view of its grea
Prior to adjustment, accounting conditions between national accounts data sets are frequently violated. Benchmarking is the procedure used by economic agencies to make such data sets consistent. It typically involves adjusting a high frequency time s
Estimation of model parameters of computer simulators, also known as calibration, is an important topic in many engineering applications. In this paper, we consider the calibration of computer model parameters with the help of engineering design know
In biomedical studies it is of substantial interest to develop risk prediction scores using high-dimensional data such as gene expression data for clinical endpoints that are subject to censoring. In the presence of well-established clinical risk fac