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Charles Rahal
Charles Rahal
Verified email at demography.ox.ac.uk - Homepage
Title
Cited by
Cited by
Year
Social network-based distancing strategies to flatten the COVID-19 curve in a post-lockdown world
P Block, M Hoffman, IJ Raabe, JB Dowd, C Rahal, R Kashyap, MC Mills
Nature Human Behaviour 4, 588–596, 2020
5612020
A scientometric review of genome-wide association studies
MC Mills, C Rahal
Communications Biology 2 (1), 9, 2019
3952019
Quantifying impacts of the COVID-19 pandemic through life-expectancy losses: a population-level study of 29 countries
JM Aburto, J Schöley, I Kashnitsky, L Zhang, C Rahal, TI Missov, MC Mills, ...
International Journal of Epidemiology 51 (1), 63-74, 2022
3602022
The GWAS Diversity Monitor tracks diversity by disease in real time
MC Mills, C Rahal
Nature Genetics 52 (3), 242-243, 2020
2012020
The decline and persistence of the old boy: Private schools and elite recruitment 1897 to 2016
A Reeves, S Friedman, C Rahal, M Flemmen
American Sociological Review 82 (6), 1139-1166, 2017
1692017
Hidden heritability due to heterogeneity across seven populations
FC Tropf, SH Lee, RM Verweij, G Stulp, PJ Van Der Most, R De Vlaming, ...
Nature Human Behaviour 1 (10), 757-765, 2017
1312017
Housing markets and unconventional monetary policy
C Rahal
Journal of Housing Economics 32, 67-80, 2016
992016
COVID-19 vaccine deployment: behaviour, ethics, misinformation and policy strategies
M Mills, C Rahal, D Brazel, J Yan, S Gieysztor
The Royal Society and The British Academy, 2020
91*2020
Face masks and coverings for the general public: behavioural knowledge, effectiveness of cloth coverings and public messaging
M Mills, C Rahal, E Akimova
The Royal Society and The British Academy: A Rapid Review, 2020
36*2020
The Keys to Unlocking Public Payments Data
C Rahal
Kyklos 71 (2), 310-337, 2018
11*2018
The Rise of Machine Learning in the Academic Social Sciences
C Rahal, MD Verhagen, D Kirk
AI & Society, 1-4, 2022
8*2022
Population Studies at 75 years: An empirical review
MC Mills, C Rahal
Population Studies 75, 7-25, 2021
52021
InterModel Vigorish (IMV): A novel approach for quantifying predictive accuracy with binary outcomes
B Domingue, C Rahal, J Faul, J Freese, K Kanopka, A Rigos, B Stenhaug, ...
SocArXiv, 2021
5*2021
Tools for Transparency in Central Government Spending
C Rahal
International Journal of Population Data Science 4 (1), 1-10, 2019
42019
The InterModel Vigorish as a lens for understanding (and quantifying) the value of item response models for dichotomously coded items
B Domingue, K Kanopka, R Kapoor, S Pohl, P Chalmers, C Rahal, ...
PsyArXiv, 2022
32022
Short Essays Written During Childhood Predict Cognition and Educational Attainment Close to or Better than Expert Assessment
T Wolfram, F Tropf, C Rahal
SocArXiv, 1-48, 2023
2*2023
The role of the third sector in public health service provision: Evidence from 25,338 heterogeneous procurement datasets
C Rahal, J Mohan
SocArXiv, 2022
22022
Outsourcing of health-care services to the private sector by English clinical commissioning groups and mortality rates, 2013–20: an observational analysis
B Goodair, A Reeves, C Rahal
The Lancet 398, S49, 2021
22021
A Guide to the StatFact EViews Add-in
C Rahal
Computational Economics, 1-6, 2015
12015
Offshoring Emissions Through used Vehicle Exports
SJ Newman, K Schulte, MM Morellini, C Rahal, DR Leasure
Nature Climate Change, 1-4, 2024
2024
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Articles 1–20