Appropriate Test Statistic

I have a data described using variable or code as indicated below. I am torn between using ANOVA Test and Chi-Square Test. Can anyone suggest which is appropriate and the reason why I need to use either for my hypothesis testing at 5% significance level to see if clearance by 14 day is affected by the (i) antibiotic used, (ii) age group of the child or (iii) ear affected.?

1-3 ID
5 Clearance by 14 days 1=yes/0=no
7 antibiotic 1 = CEF/2 = AMO
9 Age 1 = <2 yrs/2=2 - 5 yrs 3=6+ yrs
11 Ear 1=1st ear/2= 2nd ear

This seems like a classic use case for logistic regression. Your response variable is binomial

fit <- glm(clearance ~ antibiotic  + age + ear, family = binomial, data = YourData)

The summary will give you an initial read, but there's a wealth of hidden data in fit, such as confidence intervals. Save ANOVA for continuous data.

@technocrat Is there any other apart from logistic regression?

Well, it's hard for me to say without a syllabus and an understanding of your class rules of engagement.

Anova isn't designed for categorical variables. It depends on variance of continuous variables.

Chi-squared can be used for categorical variables, if you have a sufficient number of observations to be in Central Limit Theorem territory. If you have fewer than about 30 observations, you're probably in Student's t land.

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