Question

    Call:
glm(formula = Y1 ~ 0 + x1 + x2 + x3 + x4 + x5, family = quasibinomial(link = cauchit))

Deviance Residuals: 
    Min       1Q   Median       3Q      Max  
-2.5415   0.2132   0.3988   0.6614   1.8426  

Coefficients:
   Estimate Std. Error t value Pr(>|t|)    
x1  -0.7280     0.3509  -2.075  0.03884 *  
x2  -0.9108     0.3491  -2.609  0.00951 ** 
x3   0.2377     0.1592   1.494  0.13629    
x4  -0.2106     0.1573  -1.339  0.18151    
x5   3.6982     0.8658   4.271 2.57e-05 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

(Dispersion parameter for quasibinomial family taken to be 0.8782731)

    Null deviance: 443.61  on 320  degrees of freedom
Residual deviance: 270.17  on 315  degrees of freedom
AIC: NA

Number of Fisher Scoring iterations: 12

Here is the output from glm in R. Do you know a way to pull out Dispersion parameter which is 0.8782731 in this case, instead of just copy and paste. Thanks.

Was it helpful?

Solution

You can extract it from the output of summary:

data(iris)
mod <- glm((Petal.Length > 5) ~ Sepal.Width, data=iris)
summary(mod)
# 
# Call:
# glm(formula = (Petal.Length > 5) ~ Sepal.Width, data = iris)
# 
# Deviance Residuals: 
#     Min       1Q   Median       3Q      Max  
# -0.3176  -0.2856  -0.2714   0.7073   0.7464  
# 
# Coefficients:
#             Estimate Std. Error t value Pr(>|t|)
# (Intercept)  0.38887    0.26220   1.483    0.140
# Sepal.Width -0.03561    0.08491  -0.419    0.676
# 
# (Dispersion parameter for gaussian family taken to be 0.2040818)
# 
#     Null deviance: 30.240  on 149  degrees of freedom
# Residual deviance: 30.204  on 148  degrees of freedom
# AIC: 191.28
# 
# Number of Fisher Scoring iterations: 2
summary(mod)$dispersion
# [1] 0.2040818

The str function in R is often helpful to solve these sorts of questions. For instance, I looked at str(summary(mod)) to answer the question.

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