Table 3.

Accuracies for Traditional and Revised Parallel Analyses for Binary Data From the Current Study and for Continuous Data based on a Previous Study (Green et al., 2014).

	N O = 200						N O = 400
	T-PA			R-PA			T-PA			R-PA
	Binary		Normal	Binary		Normal	Binary		Normal	Binary		Normal
λ	=τ	≠τ		=τ	≠τ		=τ	≠τ		=τ	≠τ
One-factor model for all items
.5	.930	.914	.997	.952	.954	.969	.967	.956	1.000	.950	.961	.959
.7	.993	.968	1.000	.962	.966	.972	.998	.993	1.000	.959	.950	.958
One-factor model with unique items
.5	.764	.684	.850	.866	.791	.936	.845	.819	.879	.952	.935	.939
.7	.832	.777	.897	.954	.942	.936	.870	.805	.911	.949	.950	.936
Two-factor, perfect-clusters model with ρF1F2 = 0
.5	.822	.776	.984	.862	.788	.983	.949	.917	1.000	.955	.949	.997
.7	.961	.863	1.000	.962	.976	.998	.992	.968	1.000	.954	.955	1.000
Two-factor, perfect-clusters model with ρF1F2 = .5
.5	.496	.392	.876	.432	.276	.899	.808	.707	.997	.800	.683	.984
.7	.951	.873	1.000	.952	.940	.990	.994	.968	1.000	.958	.967	.998
Two-factor, perfect-clusters model with ρF1F2 = .8
.5	.098	.122	.100	.079	.060	.204	.148	.126	.187	.158	.129	.481
.7	.267	.253	.578	.421	.287	.958	.573	.510	.967	.809	.653	.988
Two-factor, bifactor model
.5	.291	.250	.610	.294	.199	.820	.587	.525	.935	.624	.522	.988
.7	.373	.284	.820	.611	.295	.982	.763	.699	.997	.901	.797	.996

Note. R-PA = revised parallel analysis; T-PA = traditional parallel analysis.