3.4 Lab

Use the transplants.dta dataset with these practice questions:

1. Calculate the standard deviation of age among patients with blood type O (abo==4). Print the following sentence: The SD of age among patients with blood type O is XX.X. Replace XX with correct values. Round to tenths (e.g. 8.2).

2. Regress BMI on age and sex (using regress bmi age gender) without displaying the regression output. Print the following sentence: Per 1-year increase in age, BMI increases by X.XX. Replace XX with the regression coefficient of age. Round to hundredths (e.g. 0.74).

   quietly regress bmi age gender
   local age_b: di %3.1f _b[age]
   
   di "Per 1-year increase in age, BMI increases by `age_b'."
   

3. Now we will do the same thing, but using a program. Define a program named bmi_age. This program will regress BMI on age and sex without displaying the regression output, and print: Per 1-year increase in age, BMI increases by X.XX. Replace XX with the regression coefficient of age. Round to hundredths (e.g. 0.74).

   capture program drop bmi_age
   program define bmi_age
   
       quietly regress bmi age gender
       local age_b: di %3.1f _b[age]
       
       di "Per 1-year increase in age, BMI increases by `age_b'."
       
   end
   

4. Let’s consider how you may allow the user of bmi_age to utilize this program on a dataset with any variable name