Beta回归:R中glmmTMB和betareg的p值不同

时间:2018-08-24 14:16:03

标签: r glm p-value betareg

我正在使用R中的betareg和glmmTMB软件包运行beta回归。系数值和AIC的结果相同,但p值不同。为什么会这样?

Betareg: beta1 <-betareg(eagtrans ~ Interspace + cover + elevation + Basal, 
           data = rall)
    > summary(beta1)

Call:
betareg(formula = eagtrans ~ Interspace + cover + elevation + 
Basal, data = rall)

Standardized weighted residuals 2:
Min      1Q  Median      3Q     Max 
-2.8165 -0.8454  0.2053  0.5900  3.9175 

Coefficients (mean model with logit link):
              Estimate Std. Error z value Pr(>|z|)    
(Intercept)      -2.418009   0.341760  -7.075 1.49e-12 ***
Interspace        0.012614   0.004326   2.916  0.00354 ** 
cover             0.039379   0.012271   3.209  0.00133 ** 
elevation        -0.433384   0.174386  -2.485  0.01295 *  
Basal            -0.033827   0.018478  -1.831  0.06715 .  

Phi coefficients (precision model with identity link):
  Estimate Std. Error z value Pr(>|z|)    
(phi)   5.9271     0.8248   7.186 6.65e-13 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Type of estimator: ML (maximum likelihood)
Log-likelihood: 87.12 on 6 Df
Pseudo R-squared: 0.1687
Number of iterations: 12 (BFGS) + 2 (Fisher scoring)

glmmTMB: beta2 <-glmmTMB(eagtrans ~ Interspace + cover + elevation + Basal, 
           data = rall, family=list(family="beta",link="logit"))
> summary(beta2)
Family: beta  ( logit )
 Formula:          eagtrans ~ Interspace + cover + elevation +  
Basal
Data: rall

     AIC      BIC   logLik deviance df.resid 
  -162.2   -146.3     87.1   -174.2      100 


Overdispersion parameter for beta family (): 5.93 

Conditional model:
             Estimate Std. Error z value Pr(>|z|)    
(Intercept)      -2.41801    0.34402  -7.029 2.08e-12 ***
Interspace        0.01261    0.00444   2.841  0.00450 ** 
cover             0.03938    0.01222   3.224  0.00127 ** 
elevation        -0.43338    0.19421  -2.232  0.02565 *  
Basal            -0.03383    0.01944  -1.740  0.08178 .  
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

这些程序包是否以不同的方式计算p值?

0 个答案:

没有答案