Adding a polygenic score as a control variable in a randomized controlled trial can be worth a 13% reduction in sample size¶

Claim · All claims
Evidence · 1 study · review r2 · q2
Currency · newest study 2017 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? Under stated assumptions, an investigator is indifferent between a larger RCT without a PGS and one 13% smaller with a PGS, at an indifference point of q = 0.87. → David Cesarini and Peter M. Visscher 2017

Evidence¶

David Cesarini and Peter M. Visscher 2017¶

David Cesarini and Peter M. Visscher. (2017). Genetics and educational attainment. npj Science of Learning 2:4. https://doi.org/10.1038/s41539-017-0005-6

q2 · i? · review · r2

Decision analysis reported from Rietveld et al. (SOM Table S27), comparing RCT designs with baseline covariates explaining 10% of outcome variance: "the investigator should be indifferent between the two options at q = 0.87", a "cost-saving equivalent to reducing the sample by 13%".

"the investigator should be indifferent between the two options at q = 0.87. Thus, the PGS in this example allows a cost-saving equivalent to reducing the sample by 13%."

Discussion¶

Related Claims¶

• A polygenic score for educational attainment explains about 15% of individual differences in out-of-sample prediction among people of European descent, with a correlation of approximately 0.4 with outcomes — a broader claim this one bears on
• Variance terms in multi-armed RCT estimators need slight adjustment under the finite-population framework, which can reduce precision — related
• Sample ancestry significantly moderates polygenic score predictions of educational attainment, with stronger predictions in European-ancestry samples — related