Application of variable selection and dimension reduction on predictors of MSE’s development

Wubetie, Habtamu Tilaye

doi:10.1186/s40537-018-0153-4

Journal of Big Data

Table 6 Logistic regression for development status of an enterprise based on selected factors through association or/union correlation methods

From: Application of variable selection and dimension reduction on predictors of MSE’s development

Variables selected by stepwise selection						Variables selected using lasso method						Reduced model
Coefficients	Estimate	Std. error	t value	\(\hbox {Pr}(>\|\hbox {t}\|)\)	Significance	Coefficients	Estimate	Std. error	t value	\(\hbox {Pr}(>\|\hbox {t}\|)\)	Significance	coefficients	Estimate	Std. error	t value	\(\hbox {Pr}(>\|\hbox {t}\|)\)	Significance
(Intercept)	− 0.735	2.857	− 0.257	0.797		(Intercept)	0.925	1.316	0.703	0.482		(Intercept)	− 0.735	2.857	− 0.257	0.797
Grouping	− 6.134	2.862	− 2.143	0.032	*	X15.29	0.091	0.283	0.322	0.747		h10	5.957	5.093	1.170	0.242
ed1	− 3.043	2.026	− 1.502	0.133		IF10	− 0.832	0.406	− 2.051	0.040	*	Grouping	− 6.134	2.862	− 2.143	0.032	*
IF8	3.209	1.421	2.258	0.024	*	ed2	0.803	0.450	1.784	0.074	.	ed1	− 3.043	2.026	− 1.502	0.133
IF10	− 4.749	1.782	− 2.665	0.008	**	Category	− 0.920	0.241	− 3.819	0.000	***	IF8	3.209	1.421	2.258	0.024	*
Category	− 0.857	0.541	− 1.584	0.113		CurrK	0.000	0.000	0.905	0.365		IF10	− 4.749	1.782	− 2.665	0.008	**
CurrK	0.000	0.000	3.059	0.002	**	h10	0.157	0.115	1.360	0.174		Category	− 0.857	0.541	− 1.584	0.113
h2	1.216	0.782	1.554	0.120		IF14	− 0.370	0.230	− 1.608	0.108		CurrK	0.000	0.000	3.059	0.002	**
StartK	0.000	0.000	− 3.039	0.002	**	MSEs	5.640	1.421	3.968	0.000	***	h2	1.216	0.782	1.554	0.120
h12	5.957	5.093	1.170	0.242		In6	− 0.491	0.598	− 0.820	0.412		StartK	0.000	0.000	− 3.039	0.002	**
c11	− 5.971	5.108	− 1.169	0.242		s4	− 1.382	0.675	− 2.046	0.041	*	c11	− 5.971	5.108	− 1.169	0.242
IF9	2.941	1.138	2.585	0.010	**	f5	0.995	0.582	1.709	0.088	.	IF9	2.941	1.138	2.585	0.010	**
IF5	− 3.468	1.262	− 2.747	0.006	**							IF5	− 3.468	1.262	− 2.747	0.006	**
s1	4.760	1.959	2.429	0.015	*							s1	4.760	1.959	2.429	0.015	*
MSEs	34.715	11.515	3.015	0.003	**							MSEs	34.715	11.515	3.015	0.003	**
s2	− 3.446	1.759	− 1.959	0.050	.							s2	− 3.446	1.759	− 1.959	0.050	.
In6	1.815	1.213	1.496	0.135								In6	1.815	1.213	1.496	0.135
In4	− 2.472	1.147	− 2.156	0.031	*							In4	− 2.472	1.147	− 2.156	0.031	*
f5	1.217	0.731	1.665	0.096	.							f5	1.217	0.731	1.665	0.096	.
h3	− 3.306	2.098	− 1.576	0.115								h3	− 3.306	2.098	− 1.576	0.115
h4	− 1.954	1.379	− 1.417	0.157								h4	− 1.954	1.379	− 1.417	0.157
AIC				84.432		AIC				106.980		AIC				84.432
Significance codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1						Significance codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1						Significance codes: 0 ‘*’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

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