How to test for a leading diagonal (home vs. away) effect with binomial data?

[janis]

I am researching if pathogens are more  or less infectious on the hosts from which they have been isolated.

So there is data on, say 4 pathogen lines (path), tested for %infection success (number diseased (d)/total inoculated(tot))) on all 4 hosts (host) from which they were originally isolated. In the infection matrix, the values on the leading diagonal are pathogens on their own hosts (home=1), while off diagonal are pathogens on novel hosts (home=0).

What model statements in GENMOD would test for a leading diagonal (home vs. away) effect?

Note:

Two approaches I tried using GENMOD give very different siginificance values

Approach 1 -

Get residuals from

     Model d/tot = path host /link=logit dist=binom p  r ;

Test home vs. away raw residuals - gives significant leading diagonal effect (P<0.02).

Visual inspection and plotting shows that the 4 leading diagonal resisduals are larger than all except one of the 12 off diagonal values, and the effect "looks real".

Approach 2 -

Compare AIC and likelihood for the above model, with the following more specified model

          d/tot = path host home/link=logi dist=binom

Home has a non-siginificant (P=0.23) effect, and comaprison of model with home included gives an AIC improvement of only 0.5, and a likelihood improvement of ca. 0.7.

So approach 2 gives no evidence of a significant leading diagonal, home vs. away effect.

The data:

Host	Path	D	H	home
1	1	12	72	1
1	2	40	36	0
1	3	11	61	0
1	4	50	29	0
2	1	10	105	0
2	2	25	85	1
2	3	3	101	0
2	4	36	78	0
3	1	20	114	0
3	2	60	76	0
3	3	11	117	1
3	4	66	63	0
4	1	20	108	0
4	2	42	76	0
4	3	7	118	0
4	4	54	70	1

[PGStats]

Hi, I assumed that Tot=D+H. After checking for interactions (home*path) and overdispersion, I arrived at the same result and conclusion as your second approach. I used proc logistic. - PG