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Statistical Analysis

QZ Qiang Zhang
MB Matthew K. Burrage
MS Mayooran Shanmuganathan
RG Ricardo A. Gonzales
EL Elena Lukaschuk
KT Katharine E. Thomas
RM Rebecca Mills
JP Joana Leal Pelado
CN Chrysovalantou Nikolaidou
IP Iulia A. Popescu
YL Yung P. Lee
XZ Xinheng Zhang
RD Rohan Dharmakumar
SM Saul G. Myerson
OR Oliver Rider
KC Keith M. Channon
SN Stefan Neubauer
SP Stefan K. Piechnik
VF Vanessa M. Ferreira
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Statistical data analysis was performed in Python (version 3.9.6) using SciPy (version 1.6.2) and Pingouin (version 0.4.0) packages. For image quality assessment and control, interobserver variability was calculated as standard deviation and intraclass correlation coefficient (ICC). The statistical significance of differences in VNE and LGE quality scores was analyzed using nonparametric Wilcoxon tests. Correlation between scar size and transmurality by VNE and LGE was assessed using linear least-squares regression (taking VNE as exposure variables, LGE as outcome variables), Pearson correlation coefficients, and ICC. The model ICC(3,k) was used to evaluate both the strength of correlation and the concordance.29 Bland-Altman analysis was performed to analyze any systematic differences between quantification by VNE and LGE. Statistical significance was defined as P<0.05.

Copyright and License information:  ©2022 The Authors.
Circulation is published on behalf of the American Heart Association, Inc., by Wolters Kluwer Health, Inc. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution, and reproduction in any medium, provided that the original work is properly cited.

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