贴个结果 看看~~~~~~

Call:
glm(formula = y ~ x1 + x2 + x3, family = binomial)

Deviance Residuals:
    Min       1Q   Median       3Q      Max  
-1.9863  -0.6675  -0.5023   0.5473   2.7843  

Coefficients:
            Estimate Std. Error z value Pr(>|z|)   
(Intercept)   0.4607     0.7066   0.652  0.51436   
x1           -3.8294     0.6025  -6.355 2.08e-10 ***
x2            1.3622     0.4729   2.881  0.00397 **
x3           -1.8487     0.5850  -3.160  0.00158 **
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

(Dispersion parameter for binomial family taken to be 1)

    Null deviance: 292.90  on 241  degrees of freedom
Residual deviance: 216.48  on 238  degrees of freedom
AIC: 224.48

Number of Fisher Scoring iterations: 5





是可以看p_value 就可以的，，比如上面的回归得到的方程就是
ln(p/(1-p)=0.4607-3.8294x1+1.3622x2-1.8487x3

Please check the book "A modern approach to regression with R" by S.J.Sheather. Section 8.1.3, 8.1.4 and 8.1.5.