Refer to Table 2.7 on x =mother’s alcohol consumption and Y =whether a baby has sex organ malformation.WIth scores (0,0.5,1.5,4.0,7.0) for alcohol consumption, ML fitting of the linear probability model has the output:a. State the prediction equation, and interpret the intercept and slope. b. Use the model fit to estimate the (i) probabilities of malformation for alcohol levels 0 and 7.0, (ii) relative risk comparing those levels.
Refer to the previous exercise1 and the solution to (b). a. The sample proportion of malformations is much higher in the highest alcohol category than the others because,although it has only one malformation, its sample size is only 38. Is the result sensitive to this single malformation observation? Re-fit the model without it (using 0 malformations in 37 observations at that level), and re-evaluate estimated probabilities of malformation at alcohol levels 0 and 7 and the relative risk. b. Is the result sensitive to the choice of scores? Re-fit the model using scores (0,1,2,3,4), and re-evaluate estimated probabilities of malformation at the lowest and highest alcohol levels and the relative risk. c. Fit a logistic regression or probit model. Report the prediction equation. Interpret the sign of the estimated effect.
The test statistic,, has a large sample chi-squared null distribution with df=?
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