value of R2 over the earlier study. The standard error of

estimate for the lung cancer equation in the present study

was slightly less than that from the earlier investigation.

 The regression equation for breast cancer in the present

study included 2 predictor variables as opposed to 23. These

2 were selected from a total of 13 independent variables

initially evaluated. The equation resulted in a value of R2

that was considerably larger than the value from the earlier

study, as well as in a smaller standard error of estimate.

 The validity of the comparison of these two sets of

results is less for the rectocolon group because the earlier

study included no cases of rectocolon cancer. However,

again, the present study used an equation with 2 as compared

to 24 variables that had a slightly lower value of R2 and a

lower standard error of estimate.

 The improved efficiency of the regression equations is

the result of the selection of a small number of relatively

powerful variables. In the present study, the identification

of these began with the methods used to code information for

important treatment variables and included the elimination of

variables with little predictive power from the regression

equations.

 In the 1974 investigation, each single treatment

modality and all interactions between treatment modalities

and other variables were used as independent variables. For