[原创][求助]新手，急求帮忙！！！

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我是新手，麻烦各位高手帮忙解决一下：以下两个表是二元logit模型的回归结果，McFadden R-squared＝0.16--0.17的结果是否可用？如果能用，那个结果更优？拜托了！！

Dependent Variable: Y
Method: ML - Binary Logit (Quadratic hill climbing)
Sample: 1 196
Included observations: 196
Variable	Coefficient	Std. Error	z-Statistic	Prob.
X1	-0.030412	0.312168	-0.097422	0.9224
X2	0.622584	0.323493	1.924565	0.0543*
X3	0.179662	0.199605	0.900086	0.3681
X4	-0.285319	0.475618	-0.599891	0.5486
X5	-0.626208	0.370960	-1.688072	0.0914*
X6	1.162410	0.615764	1.887751	0.0591*
X7	0.795024	0.239383	3.321139	0.0009**
X8	-0.815326	0.367591	-2.218022	0.0266**
X9	-0.265208	0.335939	-0.789454	0.4298
C	-4.133874	2.106255	-1.962665	0.0497
Mean dependent var	0.132653	S.D. dependent var		0.340068
S.E. of regression	0.315952	Akaike info criterion		0.750864
Sum squared resid	18.56759	Schwarz criterion		0.918115
Log likelihood	-63.58465	Hannan-Quinn criter.		0.818575
Restr. log likelihood	-76.71423	Avg. log likelihood		-0.324411
LR statistic (9 df)	26.25916	McFadden R-squared		0.171149
Probability(LR stat)	0.001853
Obs with Dep=0	170	Total obs		196
Obs with Dep=1	26

 

Dependent Variable: Y
Method: ML - Binary Logit (Quadratic hill climbing)
Sample: 1 196
Included observations: 196
Variable	Coefficient	Std. Error	z-Statistic	Prob.
X1	0.067735	0.229847	0.294696	0.7682
X2	1.005201	0.255160	3.939494	0.0001***
X3	0.094375	0.150722	0.626153	0.5312
X4	0.242213	0.339781	0.712850	0.4759
X5	-0.622816	0.295129	-2.110316	0.0348**
X6	0.561632	0.462936	1.213196	0.2251
X7	0.590912	0.179412	3.293606	0.0010***
X8	-0.619435	0.277995	-2.228223	0.0259**
X9	-0.028483	0.248594	-0.114575	0.9088
C	-4.782454	1.606787	-2.976407	0.0029
Mean dependent var	0.280612	S.D. dependent var		0.450449
S.E. of regression	0.413533	Akaike info criterion		1.089146
Sum squared resid	31.80782	Schwarz criterion		1.256397
Log likelihood	-96.73631	Hannan-Quinn criter.		1.156857
Restr. log likelihood	-116.3320	Avg. log likelihood		-0.493553
LR statistic (9 df)	39.19139	McFadden R-squared		0.168446
Probability(LR stat)	1.06E-05
Obs with Dep=0	141	Total obs		196
Obs with Dep=1	55

 

 

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