Refer to the data set EAR.DAT on the Companion Website. We will only consider a subject's first ear (`Ear=1`).

Consider a subject "cured" if

* the subject is a unilateral case and the ear clears by 14 days, or * the subject is a bilateral case and both ears are clear by 14 days.

Read the documentation on the dataset. **Delete all observations for the second ear** from the dataset before you complete the following.

## Part a (6 points)

Run a logistic regression with outcome variable `Clear` and independent variables antibiotic (`Antibo`), and age (`Age`).

Report your results by writing the logistic model in equation form. You must also clearly define the variables used in the equation (namely, the $x_i$'s).

ear.logit <- glm(Clear ~ Antibo+Age, data=ear, family=binomial) summary(ear.logit)

#P(clear)=0.2939+0.9060Antibio-1.4528Age1-0.3182Age2+epsilon

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## Part b (6 points)

What is the $OR$ for 6+ year old children vs. children younger than 2?

Write a sentence interpreting this number in the context of the problem.

#How do you create this in R

\vspace{0.75in}

## Part c (6 points)

What is the $OR$ for children receiving AMO antibiotic vs. children receiving CEF antibiotic?

Write a sentence interpreting this number in the context of the problem.

#How do you create this in R

\vspace{0.25in}

## part d (6 points) Suppose a two year old child's ear infection in the first ear was cleared within 14 days. Would you classify that child to the group who have been given an antibiotic? #How do you create this in R