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. 2019 Oct 1;7:e7829. doi: 10.7717/peerj.7829

Table 2. Factor analysis showing rotated component matrixa.

Factors
1 2 3 4 5
TLC%p 0.27 0.93 0.17 −0.10 −0.10
FRC%p −0.20 0.94 0.11 −0.13 −0.08
FRC/TLC −0.68 0.65 0.10 −0.21 −0.07
RV%p −0.07 0.89 −0.32 −0.13 −0.16
RV/TLC −0.39 0.53 −0.67 −0.16 −0.14
IC%p 0.96 .011 0.08 0.09 −0.03
IC/TLC 0.67 −0.66 −0.10 0.21 0.04
IRV%p 0.94 0.07 0.10 0.01 −0.03
IRV/TLC 0.86 −0.19 0.03 −0.01 0.13
ERV%p −0.18 0.22 0.91 −0.04 0.14
ERV/TLC −0.24 0.02 0.91 −0.03 0.09
DLCO%p 0.07 −0.25 0.19 0.18 0.92
FVC%p 0.48 −0.09 0.76 0.12 −0.04
FEV1%p 0.37 −0.26 0.54 0.65 0.06
FEV1/FVC −0.00 −0.22 −0.04 0.94 0.15
SVC%p 0.57 0.06 0.77 0.08 0.04

Notes.

For all abbreviations, please refer to Table 1. Extraction method: Principal component analysis. Rotation method: Varimax with Kaiser normalization.

a

Rotation converged in 5 iterations.

Bolded number indicating the important variables (arbitrarily defined as value >0.85) in that factor, Italic number indicating the variables with moderate importance (arbitrarily defined as value > 0.50) in that factor.