Statistical Analysis Code.

<div><p>Taylor Swift’s presence at National Football League (NFL) games was reported to have a causal effect on the performance of Travis Kelce and the Kansas City Chiefs. Critical examination of the supposed “Swift effect” provides some surprising lessons relevant to the scientific comm...

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Bibliographic Details
Main Author:	James M. Smoliga (9074225) (author)
Other Authors:	Kathryn E. Sawyer (22278038) (author)
Published:	2025
Subjects:	Medicine Sociology Science Policy using covariate matching national football league kansas city chiefs avoid falling victim chiefs &# 8217 chief &# 8217 scrutinize available evidence supposed &# 8220 purported &# 8220 kelce &# 8217 swift &# 8221 swift &# 8217 research &# 8211 weak statistical evidence 6 games ), surprising lessons relevant matching algorithm used effect &# 8211 games without swift &# 8220 robust evidence travis kelce swift games statistical significance taylor swift medical research clinical research 13 games unjustified theories unjustified mechanisms surrogate outcomes since failure significantly differ significant increase scientific journalism scientific community researchers must medical journalism media narrative indicating inconsistency inadequate sampling historical data historical averages game outcomes formal analysis findings suggest finding varied fallacies common experimental study draw parallels
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Statistical Analysis Code.

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