Table 7 Ordered logistic regression for...

Table 7

Ordered logistic regression for survival-oriented company goals

	Variables	Model 1 (y₁)		Model 2 (y₂)		Model 3 (y₃)		Model 4 (y₄)		Model 5 (y₅)
	Variables	$β$	Z	$β$	Z	$β$	Z	$β$	Z	$β$	Z
	x₁	−0.002	−0.03	0.023	0.28	−0.010	−0.09	−0.058	−0.69	−0.076	−0.97
	x₂	0.025	0.36	0.074	0.97	0.029	0.27	0.024	0.32	0.042	0.59
	x₃	−0.106	−1.05	−0.238^**	−2.34	−0.033	−0.21	−0.104	−0.95	−0.073	−0.74
	x₄	0.067	0.92	0.129^*	1.66	0.069	0.64	0.121	1.58	0.095	1.33
	x₅	0.051	0.76	0.002	0.04	0.191^**	1.99	0.032	0.47	0.024	0.38
	x₆	0.161^**	2.39	0.006	0.09	−0.048	−0.51	0.059	0.85	−0.049	−0.78
	x₇	0.416	0.87	0.912^*	1.89	0.576	0.84	0.121	0.24	−0.677	−1.37
	x₈	0.336	1.56	0.008	0.04	0.024	0.08	0.317	1.43	0.157	0.78
	x₉	−0.904^*	−1.67	−0.845	−1.56	1.038	0.94	−1.267^**	−2.14	−0.247	−0.47
	x₁₀	0.587	0.98	0.010	0.02	0.066	0.08	−0.259	−0.46	1.148^*	1.85
	/cut1	−0.586		−2.215		−2.665		−2.157		−2.392
	/cut2	−0.022		−1.485		−2.372		−1.602		−1.789
	/cut3	0.272		−0.968		−1.953		−1.140		−1.419
	/cut4	0.919		−0.255		−1.309		−0.628		−1.045
	/cut5	1.545		0.547		−0.148		0.188		−0.634
	/cut6	2.165		1.206				0.999		−0.212
	Log likelihood	−249.668		−237.851		−110.072		−224.884		−293.946
	LR χ² (10)	19.31		16.59		8.05		11.76		9.47
	Prob > χ²	0.0364		0.0839		0.6242		0.3017		0.4878
R2	McFadden	0.037		0.034		0.035		0.025		0.016
	McFadden(adjusted)	−0.024		−0.031		−0.096		−0.044		−0.038
	McKelvey and Zavoina	0.122		0.097		0.104		0.078		0.056
	Cox–Snell/ML	0.103		0.089		0.044		0.064		0.052
	Cragg–Uhler/Nagelkerke	0.109		0.095		0.061		0.069		0.054
	Count	0.539		0.562		0.831		0.590		0.438
	Count (adjusted)	0.000		0.013		0.000		0.000		0.000
IC	AIC	531.337		507.703		250.146		481.769		619.893
	AIC divided by N	2.985		2.852		1.405		2.707		3.483
	BIC (df = 16)	582.246		558.612		297.873		532.677		670.801

	Variables	Model 1 (y₁)		Model 2 (y₂)		Model 3 (y₃)		Model 4 (y₄)		Model 5 (y₅)
	Variables	$β$	Z	$β$	Z	$β$	Z	$β$	Z	$β$	Z
	x₁	−0.002	−0.03	0.023	0.28	−0.010	−0.09	−0.058	−0.69	−0.076	−0.97
	x₂	0.025	0.36	0.074	0.97	0.029	0.27	0.024	0.32	0.042	0.59
	x₃	−0.106	−1.05	−0.238^**	−2.34	−0.033	−0.21	−0.104	−0.95	−0.073	−0.74
	x₄	0.067	0.92	0.129^*	1.66	0.069	0.64	0.121	1.58	0.095	1.33
	x₅	0.051	0.76	0.002	0.04	0.191^**	1.99	0.032	0.47	0.024	0.38
	x₆	0.161^**	2.39	0.006	0.09	−0.048	−0.51	0.059	0.85	−0.049	−0.78
	x₇	0.416	0.87	0.912^*	1.89	0.576	0.84	0.121	0.24	−0.677	−1.37
	x₈	0.336	1.56	0.008	0.04	0.024	0.08	0.317	1.43	0.157	0.78
	x₉	−0.904^*	−1.67	−0.845	−1.56	1.038	0.94	−1.267^**	−2.14	−0.247	−0.47
	x₁₀	0.587	0.98	0.010	0.02	0.066	0.08	−0.259	−0.46	1.148^*	1.85
	/cut1	−0.586		−2.215		−2.665		−2.157		−2.392
	/cut2	−0.022		−1.485		−2.372		−1.602		−1.789
	/cut3	0.272		−0.968		−1.953		−1.140		−1.419
	/cut4	0.919		−0.255		−1.309		−0.628		−1.045
	/cut5	1.545		0.547		−0.148		0.188		−0.634
	/cut6	2.165		1.206				0.999		−0.212
	Log likelihood	−249.668		−237.851		−110.072		−224.884		−293.946
	LR χ² (10)	19.31		16.59		8.05		11.76		9.47
	Prob > χ²	0.0364		0.0839		0.6242		0.3017		0.4878
R2	McFadden	0.037		0.034		0.035		0.025		0.016
	McFadden(adjusted)	−0.024		−0.031		−0.096		−0.044		−0.038
	McKelvey and Zavoina	0.122		0.097		0.104		0.078		0.056
	Cox–Snell/ML	0.103		0.089		0.044		0.064		0.052
	Cragg–Uhler/Nagelkerke	0.109		0.095		0.061		0.069		0.054
	Count	0.539		0.562		0.831		0.590		0.438
	Count (adjusted)	0.000		0.013		0.000		0.000		0.000
IC	AIC	531.337		507.703		250.146		481.769		619.893
	AIC divided by N	2.985		2.852		1.405		2.707		3.483
	BIC (df = 16)	582.246		558.612		297.873		532.677		670.801

Note(s): ^**p-value $\leq$ 0.05, ^*p-value $\leq$ 0.1

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