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Table 1 Two-dimensional factor loadings and Rasch item difficulty and mean squares fit statistics for both 1-dimensional and 2-dimensional usages

From: A closer look at the items within three measures of evolution acceptance: analysis of the MATE, I-SEA, and GAENE as a single corpus of items

Item Wording EFA dimensionality 1D 1D 1D 2D 2D 2D
F1 loading F2 loading Difficulty Infit Outfit Difficulty Infit Outfit
ISEAMacro1 P 0.87 − 0.03 − 0.17 0.67 0.63 − 0.15 0.70 0.68
ISEAMacro2a N 0.12 0.62 0.15 1.25 1.72 0.06 1.05 1.16
ISEAMacro3 P 0.70 0.15 − 0.33 0.62 0.62 − 0.33 0.72 0.75
ISEAMacro4 P 0.77 − 0.05 0.39 0.95 1.07 0.53 1.05 1.17
ISEAMacro5 P 0.72 0.08 − 0.32 0.75 0.78 − 0.33 0.83 0.88
ISEAMacro6 N 0.23 0.58 0.28 0.93 0.95 0.19 0.82 0.84
ISEAMacro7 P 0.71 0.05 − 0.36 0.73 0.73 − 0.38 0.84 0.82
ISEAMacro8b P 0.78 − 0.13 0.27 1.14 1.29 0.39 1.23 1.37
ISEAMicro1a N − 0.17 0.83 − 0.18 1.22 1.39 − 0.31 0.92 1.15
ISEAMicro2 P 0.61 0.04 − 0.52 0.96 1.03 − 0.57 1.12 1.17
ISEAMicro3b P 0.37 0.24 − 0.68 1.07 0.92 − 0.77 1.32 1.17
ISEAMicro4a N − 0.26 0.92 − 0.24 1.44 1.74 − 0.36 0.97 1.02
ISEAMicro5 N − 0.06 0.82 − 0.26 1.11 1.10 − 0.39 0.83 0.95
ISEAMicro6 P 0.50 0.15 − 0.34 0.89 0.91 − 0.35 1.06 1.06
ISEAMicro7a N − 0.04 0.78 − 0.39 1.33 1.30 − 0.52 0.97 0.91
ISEAMicro8 P 0.72 0.07 − 0.14 0.76 0.72 − 0.11 0.83 0.79
ISEAHuman1 P 0.81 0.01 0.19 0.78 0.80 0.29 0.81 0.84
ISEAHuman2 N 0.24 0.58 0.46 1.08 1.12 0.38 1.01 1.01
ISEAHuman3 N 0.23 0.61 0.26 1.04 1.03 0.18 0.90 0.90
ISEAHuman4 P 0.85 − 0.01 0.17 0.95 0.95 0.27 0.99 0.99
ISEAHuman5 P 0.73 0.08 − 0.02 1.01 0.98 0.03 1.18 1.17
ISEAHuman6 N 0.11 0.67 0.09 1.15 1.23 − 0.01 0.95 1.04
ISEAHuman7 P 0.84 − 0.02 0.08 0.90 0.95 0.16 0.92 0.96
ISEAHuman8 P 0.63 − 0.10 − 0.15 1.00 1.08 − 0.11 1.15 1.18
MATEfacts1 P 0.82 0.07 − 0.13 0.68 0.62 − 0.09 0.71 0.65
MATEcred2 N 0.07 0.65 0.27 1.21 1.22 0.18 1.02 1.06
MATEfacts3 P 0.87 − 0.01 0.09 0.80 0.75 0.18 0.84 0.79
MATEcred4 N 0.12 0.66 0.26 1.08 1.17 0.16 0.94 0.97
MATEcred5b P 0.46 0.05 − 0.50 1.12 1.23 − 0.56 1.33 1.39
MATEcred6 N 0.28 0.50 0.46 0.91 1.00 0.40 0.85 0.90
MATEcred7a N 0.07 0.59 − 0.31 1.48 1.46 − 0.43 1.24 1.23
MATEfacts8 P 0.73 0.09 − 0.15 0.68 0.65 − 0.13 0.77 0.74
MATEcred9a N 0.03 0.73 − 0.07 1.29 1.47 − 0.18 0.99 0.99
MATEcred10 N 0.21 0.63 − 0.03 1.00 1.02 − 0.13 0.90 0.87
MATEfacts11 P 0.64 0.10 − 0.15 1.05 1.06 − 0.12 1.21 1.16
MATEfacts12 P 0.70 0.09 0.04 0.69 0.72 0.11 0.78 0.94
MATEfacts13 P 0.79 − 0.01 − 0.04 0.71 0.84 0.01 0.76 0.91
MATEcred14 N 0.14 0.69 0.13 1.22 1.26 0.03 1.04 1.03
MATEfacts15a N 0.10 0.69 0.20 1.28 1.32 0.11 1.02 1.01
MATEfacts16 P 0.73 0.10 0.11 0.78 0.76 0.20 0.85 0.84
MATEcred17a,b N − 0.22 0.69 0.22 1.58 1.79 0.12 1.31 1.53
MATEfacts18 P 0.80 0.06 − 0.11 0.61 0.59 − 0.07 0.66 0.63
MATEcred19a,b N − 0.05 0.56 0.58 1.43 2.01 0.52 1.25 1.54
MATEfacts20 P 0.64 0.24 − 0.01 0.72 0.70 0.05 0.87 0.88
GAENE1a,b P 0.60 − 0.03 − 0.24 1.23 1.36 − 0.23 1.42 1.52
GAENE2 P 0.66 0.14 − 0.03 0.72 0.74 0.02 0.84 0.85
GAENE3b P 0.54 0.07 − 0.70 1.04 1.28 − 0.80 1.21 1.36
GAENE4 P 0.81 0.01 − 0.27 0.96 0.89 − 0.27 1.03 0.96
GAENE5 P 0.69 0.02 − 0.51 0.98 0.98 − 0.57 1.08 1.08
GAENE6b P 0.73 − 0.05 0.84 1.20 1.29 1.08 1.28 1.51
GAENE7 P 0.53 0.05 − 0.73 1.06 1.06 − 0.83 1.23 1.21
GAENE8a,b P 0.79 − 0.19 0.92 1.18 1.50 1.18 1.30 1.69
GAENE9 P 0.81 − 0.03 0.15 0.84 0.85 0.24 0.89 0.87
GAENE10 P 0.73 0.08 0.52 1.03 1.05 0.69 1.11 1.17
GAENE11 P 0.91 − 0.07 0.36 0.92 0.92 0.49 0.93 0.94
GAENE12 P 0.78 − 0.07 0.71 1.09 1.15 0.93 1.15 1.19
GAENE13 P 0.79 0.08 − 0.10 0.69 0.64 − 0.07 0.73 0.68
  1. aPotential item misfit with the Rasch model in a unidimensional treatment
  2. bPotential item misfit with the Rasch model in a two-dimensional treatment