Towards Statistical Best Practices for Gender and Sex Data-Reference-Cited by-同舟云学术

Towards Statistical Best Practices for Gender and Sex Data

Published:2022-01-25 Issue:1 Volume:19 Page:40-45
ISSN:1740-9705
Container-title:Significance
language:en
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Author:

Thornton Suzanne¹,Roy Dooti²,Parry Stephen³,LaLonde Donna⁴,Martinez Wendy⁵,Ellis Renee⁶,Corliss David⁷

Affiliation:

1. Suzanne Thornton is assistant professor of statistics in the Mathematics and Statistics Department, Swarthmore College

2. Dooti Roy is senior principal therapeutic area methodology statistician at Boehringer Ingelheim

3. Stephen Parry is a statistical consultant at Cornell University

4. Donna LaLonde is director of strategic initiatives and outreach at the American Statistical Association

5. Wendy Martinez is director of the Mathematical Statistics Research Center at the Bureau of Labor Statistics

6. Renee Ellis is a research methodologist at the US Census Bureau

7. David Corliss is director of Peace-Work

Abstract

Abstract Suzanne Thornton, Dooti Roy, Stephen Parry, Donna LaLonde, Wendy Martinez, Renee Ellis and David Corliss call for a more inclusive – and informative – approach to collecting data on human gender and sex

Publisher

Oxford University Press (OUP)

Subject

Statistics and Probability

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/1740-9713.01614

Reference15 articles.

1. Gender-related variables for health research;Nielsen;Biology of Sex Differences,2021

2. Third Sex, Third Gender

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4. Consensus statement on management of intersex disorders;Hughes;Journal of Pediatric Urology,2006

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