Table 1.

Accuracy and Bias of the Factor Retention Criteria for Ordinal Indicators, Symmetric Thresholds and Different Numbers of Categories.

Method	Acc	Acc 2−Cat	Bias 2−Cat	Acc 3−Cat	Bias 3−Cat	Acc 4−Cat	Bias 4−Cat	Acc 5−Cat	Bias 5−Cat	Acc 6−Cat	Bias 6−Cat
FF	0.891	0.803	0.021	0.888	0.027	0.913	0.029	0.924	0.034	0.929	0.033
PA	0.807	0.727	−0.538	0.803	−0.412	0.828	−0.369	0.838	−0.350	0.842	−0.342
CD	0.692	0.550	−1.654	0.693	−1.006	0.730	−0.839	0.743	−0.727	0.746	−0.654
EKC	0.647	0.645	−0.812	0.651	−0.996	0.647	−1.031	0.645	−1.049	0.645	−1.057
KG	0.550	0.434	1.675	0.532	1.046	0.576	0.843	0.596	0.744	0.610	0.690

Note. Acc stands for accuracy - so Acc_2−Cat stands for the accuracy in conditions based on ordinal indicators with two levels (and symmetric thresholds). Bias describes the mean deviation of the suggested number of factors from the true number of factors in the respective conditions.

FF = Factor Forest; CD = Comparison Data; EKC = empirical Kaiser criterion; KG = Kaiser–Guttman rule.