hi, people
    How can we compare two probit models brought out from the same data?
    Let me use the example used in "An Introduction to R".
    "Consider a small, artificial example, from Silvey (1970).

On the Aegean island of Kalythos the male inhabitants suffer from a
congenital eye disease, the effects of which become more marked with
increasing age. Samples of islander males of various ages were tested for
blindness and the results recorded. The data is shown below:

Age: 20 35 45 55 70
No. tested: 50 50 50 50 50
No. blind: 6 17 26 37 44
"

now, we can use the age and the blind percentage to produce a probit model
and get their coefficients by using glm function as was did in "An
Introduction to R"

My question is, let say there is another potential factor instead of age
affected the blindness percentage.
for example, the height of these males. Using their height, and their
relevant blindness we can introduce another probit model.

If I want to determine which is significantly better, which function can I
use to compare both models? and, in addition, compared with the Null
hypothesis(i.e. the same blindness for all age/height) to prove this model
is effective?

	[[alternative HTML version deleted]]


