[R] paradox about the degree of freedom in a logistic regression model

From: Bin Yue <leffgh_at_163.com>
Date: Thu, 6 Dec 2007 23:55:23 -0800 (PST)

 Dear all:
   "predict.glm" provides an example to perform logistic regression when the response variable is a tow-columned matrix. I find some paradox about the degree of freedom .
> summary(budworm.lg)

Call:
glm(formula = SF ~ sex * ldose, family = binomial)

Deviance Residuals:

     Min 1Q Median 3Q Max -1.39849 -0.32094 -0.07592 0.38220 1.10375

Coefficients:

            Estimate Std. Error z value Pr(>|z|)    
(Intercept)  -2.9935     0.5527  -5.416 6.09e-08 ***
sexM          0.1750     0.7783   0.225    0.822    
ldose         0.9060     0.1671   5.422 5.89e-08 ***
sexM:ldose    0.3529     0.2700   1.307    0.191    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

(Dispersion parameter for binomial family taken to be 1)

    Null deviance: 124.8756  on 11  degrees of freedom
Residual deviance:   4.9937  on  8  degrees of freedom
AIC: 43.104

Number of Fisher Scoring iterations: 4

This is the data set used in regression:
  numdead numalive sex ldose
1        1       19   M     0
2        4       16   M     1
3        9       11   M     2
4       13        7   M     3
5       18        2   M     4
6       20        0   M     5
7        0       20   F     0
8        2       18   F     1
9        6       14   F     2
10      10       10   F     3
11      12        8   F     4
12      16        4   F     5

     The degree of freedom is 8. Each row in the example is thought to be
one observation. If  I extend it to be a three column data.frame, the first
denoting the whether the individual is alive , the secode denoting the sex,
and the third "ldose",there will be 12*20=240 observations. 
     Since my data set is one of the second type , I wish to know whether
the form of data set affects the result of regression ,such as the degree of
freedom.
   Dose anybody have any idea about this? Thank all who read this message.
   Regards,
   Bin Yue

-----
Best regards,
Bin Yue

*************
student for a Master program in South Botanical Garden , CAS

-- 
View this message in context: http://www.nabble.com/paradox-about-the-degree-of-freedom-in-a-logistic-regression-model-tf4960753.html#a14208306
Sent from the R help mailing list archive at Nabble.com.

______________________________________________
R-help_at_r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
Received on Fri 07 Dec 2007 - 08:00:20 GMT

Archive maintained by Robert King, hosted by the discipline of statistics at the University of Newcastle, Australia.
Archive generated by hypermail 2.2.0, at Fri 07 Dec 2007 - 14:30:17 GMT.

Mailing list information is available at https://stat.ethz.ch/mailman/listinfo/r-help. Please read the posting guide before posting to the list.