Table 4.11 shows estimated effects for a logistic regression model for y = presence of squamous cell esophageal cancer (1 = yes, 0 = no). Smoking status (s) equals 1 for at least one pack per day and 0 otherwise, alcohol consumption

(a) equals the average number of alcoholic drinks consumed per day, and race (r) equals 1 for blacks and 0 for whites.

a. To describe the race-by-smoking interaction, construct the prediction equation when r = 1 and again when r = 0. Find the fitted conditional odds ratio for the smoking effect for each case. Similarly, construct the prediction equation when s = 1 and again when s = 0. Find the fitted conditional odds ratio for the race effect for each case. (For each association, the coefficient of the cross-product term is the difference between the log odds ratios at the two levels for the other variable.)

b. In Table 4.11, what do the coefficients of smoking and race represent? What hypotheses do their P-values refer to?

Table 4.11 Table for Exercise