R中的负二项式模型

通过使用以下代码,我在R中运行了负二项式模型。

myModel <- glm.nb(V7 ~ V11 + V8 + V3 + V10 + V12 + V5, data = data)
summary(myModel)

V7是因变量。其他变量是自变量。

我得到以下输出。但是R输出不同于Stata输出。我应该怎么做才能解决这个问题?

Call:
glm.nb(formula = V7 ~ V11 + V8 + V3 + V10 + V12 + V5, data = data, 
    init.theta = 0.4931977401, link = log)

Deviance Residuals: 
    Min       1Q   Median       3Q      Max  
-1.3363  -1.0487  -0.7826   0.1631   2.4126  

Coefficients:
              Estimate Std. Error z value Pr(>|z|)    
(Intercept) -7.046e-01  3.824e-01  -1.842 0.065408 .  
V11         -1.705e-01  2.909e-01  -0.586 0.557875    
V8          -1.549e-06  4.371e-06  -0.354 0.723149    
V3           4.525e-02  1.168e-02   3.873 0.000108 ***
V10          3.050e-04  3.275e-03   0.093 0.925802    
V12         -1.965e-03  6.121e-03  -0.321 0.748157    
V5           5.378e-03  5.954e-03   0.903 0.366423    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

(Dispersion parameter for Negative Binomial(0.4932) family taken to be 1)

    Null deviance: 270.87  on 285  degrees of freedom
Residual deviance: 233.16  on 279  degrees of freedom
AIC: 726.49

Number of Fisher Scoring iterations: 1


              Theta:  0.4932 
          Std. Err.:  0.0922 

 2 x log-likelihood:  -710.4890 
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