做logit回归出来以下结果,这里的McFadden R方要怎么看?0.4几会不会太小呢?是截面数据
Dependent Variable: SER01
Method: ML - Binary Logit (Quadratic hill climbing)
Date: 03/03/13 Time: 19:41
Sample: 1 153
Included observations: 153
Convergence achieved after 9 iterations
Covariance matrix computed using second derivatives
Coefficient Std. Error z-Statistic Prob.
C 4.078715 2.306311 1.768502 0.0770
SER02 0.001291 0.001589 0.812241 0.4167
SER03 -0.073015 0.112738 -0.647652 0.5172
SER04 3.170781 2.292626 1.383035 0.1667
SER05 -8.333441 5.536509 -1.505180 0.1323
SER06 -4.297509 1.678385 -2.560503 0.0105
SER07 1.172112 3.683587 0.318199 0.7503
SER08 0.074188 1.219338 0.060843 0.9515
SER09 -0.018253 0.008196 -2.227205 0.0259
SER10 0.014676 0.058556 0.250633 0.8021
McFadden R-squared 0.480634 Mean dependent var 0.686275
S.D. dependent var 0.465530 S.E. of regression 0.340077
Akaike info criterion 0.776861 Sum squared resid 16.53825
Schwarz criterion 0.974929 Log likelihood -49.42990
Hannan-Quinn criter. 0.857320 Restr. log likelihood -95.17352
LR statistic 91.48723 Avg. log likelihood -0.323071
Prob(LR statistic) 0.000000
Obs with Dep=0 48 Total obs 153
Obs with Dep=1 105