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07-23-2010 02:22 PM

Hi. I have not built models in SAS before, but any help would be greatly appreciated. Ultimately, I would like to find the optimal "score" values in the following table:

age_LB | age_UB | score

20 | 29 | 20

30 | 39 | 30

40 | 49 | 40

A score gets assigned depending on the age of the person according to the values above. The dataset would look something like this:

name | age | GB | Score

peter | 21 | G | 20

jo | 31 | G | 30

mary | 41 | G | 40

sam | 21 | B | 20

paul | 31 | B | 30

jane | 41 | B | 40

Now what I need to do is to change the scores in the first table such that the following statistic is maximized:

(Mean_G - Mean_B)^2/(0.5*(Variance_G^2 + Variance_B^2))

where Mean_G is the mean score for the "G"'s, etc.

Also, there is also a criterion that the scores must not decrease as the age increases and they cannot be negative (e.g. the scores must go 20 < 30 < 40).

Any ideas on how to go about tackling this problem? Thanks very much!

age_LB | age_UB | score

20 | 29 | 20

30 | 39 | 30

40 | 49 | 40

A score gets assigned depending on the age of the person according to the values above. The dataset would look something like this:

name | age | GB | Score

peter | 21 | G | 20

jo | 31 | G | 30

mary | 41 | G | 40

sam | 21 | B | 20

paul | 31 | B | 30

jane | 41 | B | 40

Now what I need to do is to change the scores in the first table such that the following statistic is maximized:

(Mean_G - Mean_B)^2/(0.5*(Variance_G^2 + Variance_B^2))

where Mean_G is the mean score for the "G"'s, etc.

Also, there is also a criterion that the scores must not decrease as the age increases and they cannot be negative (e.g. the scores must go 20 < 30 < 40).

Any ideas on how to go about tackling this problem? Thanks very much!