R help - Feb 2011 - 3 questions about the poisson regression of contingency table

Hi all:
I have 3 questions about the poisson regression of contingency table.

Q1¡¢How to understand the "independent poisson process"as many books
or paper
mentioned?
    For instance:

   Table1
   -------------------------------------------
   treat      caner    non-cancer    sum
   -------------------------------------------
   treat1     52(57.18)   19(13.82)     71
   treat2     39(33.82)   3 (8.18)      42
   -------------------------------------------
   sum       91          22            113
   -------------------------------------------
   The numbers in parentheses are the expected frequency,which are computed
by(57.18 for instance):
   71*91/113=57.18

   But according to poisson distribution,the distribution function is:
   pr<-exp(-mu)*mu^x/x!.But I can't find this function in the computation
of
expected frequency of Table1.
   In other words,how the underdstand the"independent poisson process"
from
Table1?

Q2¡¢How to understand "zero-inflated"?
    For instance:
 area nation frequency
 1 1 10
 1 2 0
 1 3 0
 1 4 0
 2 1 20
 2 2 0
 2 3 0
 2 4 5
 3 1 15
 3 2 6
 3 3 20
 3 4 0

Since most of the frequencies(6/12) are zero,so I can simply consider the
dataset is "zero-inflated"?
In other words, can I judge the dataset is "zero-inflated" simply by
the
proportion of "zero frequency"?
Or,how to judge whether the dataset is "zero-inflated" or not?


Q3¡¢How to understand "over-dispersion"?
    For instance:
 area nation frequency
 1 1 10
 1 2 0
 1 3 0
 1 4 0
 2 1 20
 2 2 0
 2 3 0
 2 4 5
 3 1 15
 3 2 6
 3 3 20
 3 4 0

Obviously, the frequencies' distribution is of great skewness.So can I judge
the dataset is "over-dispersion"?
In other words, can I judge the dataset is "over-dispersion" simply by
the
distribution of all the frequencies?
Or,how to judge whether the dataset is "over-dispersion" or not?


Thanks a lot for your help.

My best.

	[[alternative HTML version deleted]]

Hi all:
I have 3 questions about the poisson regression of contingency table.
Q1¡¢How to understand the "independent poisson process"as many books
or paper
mentioned?
    For instance:
   Table1
   -------------------------------------------
   treat      caner    non-cancer    sum
   -------------------------------------------
   treat1     52(57.18)   19(13.82)     71
   treat2     39(33.82)   3 (8.18)      42
   -------------------------------------------
   sum       91          22            113
   -------------------------------------------
   The numbers in parentheses are the expected frequency,which are computed
by(57.18 for instance):
   71*91/113=57.18

   But according to poisson distribution,the distribution function is:
   pr<-exp(-mu)*mu^x/x!.But I can't find this function in the computation
of
expected frequency of Table1.
   In other words,how the underdstand the"independent poisson process"
from
Table1?
Q2¡¢How to understand "zero-inflated"?
    For instance:
 area nation frequency
 1 1 10
 1 2 0
 1 3 0
 1 4 0
 2 1 20
 2 2 0
 2 3 0
 2 4 5
 3 1 15
 3 2 6
 3 3 20
 3 4 0
Since most of the frequencies(6/12) are zero,so I can simply consider the
dataset is "zero-inflated"?
In other words, can I judge the dataset is "zero-inflated" simply by
the
proportion of "zero frequency"?
Or,how to judge whether the dataset is "zero-inflated" or not?

Q3¡¢How to understand "over-dispersion"?
    For instance:
 area nation frequency
 1 1 10
 1 2 0
 1 3 0
 1 4 0
 2 1 20
 2 2 0
 2 3 0
 2 4 5
 3 1 15
 3 2 6
 3 3 20
 3 4 0
Obviously, the frequencies' distribution is of great skewness.So can I judge
the dataset is "over-dispersion"?
In other words, can I judge the dataset is "over-dispersion" simply by
the
distribution of all the frequencies?
Or,how to judge whether the dataset is "over-dispersion" or not?

Thanks a lot for your help.
My best.

	[[alternative HTML version deleted]]