PLS and Functional Neuroimaging: Bias and Detection Power Across Different Resampling Schemes

DOI10.1007/978-3-319-40643-5_7zbMath1367.62290OpenAlexW2531413173WikidataQ57089003 ScholiaQ57089003MaRDI QIDQ5278361

Stephen C. Strother, Babak Afshin-Pour, Nathan W. Churchill

Publication date: 19 July 2017

Published in: Springer Proceedings in Mathematics & Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-319-40643-5_7

zbMATH Keywords

predictionbootstrapPCAreproducibility\(f\) MRIbehavioral PLSsplit-half resampling

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Applications of statistics to biology and medical sciences; meta analysis (62P10) Measures of association (correlation, canonical correlation, etc.) (62H20)

Cites Work

• New perspectives in partial least squares and related methods. Based on the presentation at the 7th partial least squares (PLS) conference, Houston, TX, USA, May 19--22, 2012

This page was built for publication: PLS and Functional Neuroimaging: Bias and Detection Power Across Different Resampling Schemes