On 3 May 2001 09:46:12 -0700, [EMAIL PROTECTED] (R. Mark Sharp; Ext.
476) wrote:
> If there is a better venue for this question, please advise me.
- an epidemiology mailing list?
[ snip, much detail ]
> Time point 1 Time point 2 Time point 3 Time point 4 Hosts
> Inf Not-Inf Inf Not-Inf Inf Not-Inf Inf Not-Inf Tested
>
> G1-S1 1 14 11 4 11 1 13 2 57
> G1-S2 7 8 12 3 14 2 15 8 69
> G1-S3 1 24 6 18 8 15 9 15 95
>
> G2-S4 3 12 12 4 10 4 14 2 61
> G2-S5 5 10 5 6 8 7 11 14 57
> G2-S6 2 26 12 12 11 16 14 12 105
>
> The questions are how can group 1 (G1) be compare to group 2 (G2) and
> how can subgroups be compared. I maintain that the heterogeneity
> within each group does not prevent pooling of the subgroup data
> within each group, because the groupings were made a priori based on
> genetic similarity.
Mostly, heterogeneity prevents pooling.
What's an average supposed to mean?
Only if the Ns represent naturally-occurring proportions,
and so does your hypothesis, then you MIGHT want to
analyze the numbers that way.
How much do you know about the speed of expected onset,
and offset of the disease? If this were real, It looks to me like you
would want special software. Or special evaluation of a likelihood
function.
I can put the hypothesis in simple ANOVA terms, comparing species
(S). Then, the within-Variability of G1 and G2 -- which is big --
would be used to test the difference Between: according to some
parameter. Would that be an estimate of "maximum number afflicted"?
--
Rich Ulrich, [EMAIL PROTECTED]
http://www.pitt.edu/~wpilib/index.html
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