Table 7. Logistic regression analyses: Predicting pass rates for basic course based on K-PAT subtest scores

		B	SE	Wald	p	df	OR	OR 95% 신뢰구간
								하한	상한
인지영역	→기본 과정 수료
도형회전		0.031	.100	0.096	.756	1	1.032	0.848	1.255
도형전개도		0.226*	.102	4.911	.027	1	1.253	1.026	1.530
척도판독		0.095	.099	0.922	.337	1	1.100	0.906	1.335
계기판독		0.375***	.105	12.639	<.001	1	1.455	1.183	1.789
배관미로		-0.362***	.096	14.165	<.001	1	0.696	0.577	0.841
기계원리		0.133	.101	1.727	.189	1	1.143	0.937	1.394
의사결정		0.021	.095	0.049	.825	1	1.021	0.847	1.231
시각변별		0.043	.091	0.224	.636	1	1.044	0.873	1.249
기억		-0.172	.123	1.957	.162	1	0.842	0.662	1.071
정보처리영역
수표해독		0.124	.077	2.569	.109	1	1.132	0.973	1.318
속도추정		-0.242*	.117	4.294	.038	1	0.785	0.624	0.987
추적/회피		-0.462***	.139	11.017	<.001	1	0.630	0.479	0.827
멀티태스킹(이동)		0.061	.097	0.395	.530	1	1.063	0.879	1.285
멀티태스킹(기억)		0.254**	.089	8.172	.004	1	1.289	1.083	1.535
멀티태스킹(청각)		0.242**	.085	8.076	.004	1	1.273	1.078	1.504
χ2(15) = 112.733 (p<.001), Nagelkerke R2 = .186, 분류정확도 = 73.9%

주: p<.05,
p<.01,
p<.001.