Lab 1#

Part 1#

Write Stata commands to solve the following questions. Keep them in a .txt or .docx file. In the second half of today’s class you will learn how to put them in a .do file or script to run all of the commands at the same time. For now, put them in a text file and copy & paste one line at a time into Stata to get the answers.

You will turn this work in together with Lab 1 Part 2.

Write Stata commands to answer the following questions about the dataset transplants.dta:

  1. How many total patients are in the dataset?

  2. The variable dx represents diagnosis and age represents patient age. How many patients were between the ages of 50 and 60 and had diabetes as their primary diagnosis at the time of transplant?

  3. The variable wait_yrs represents the amount of time a patient spent on the transplant waitlist prior to transplant. How many patients waited longer than 5 years for a transplant?

  4. What is the age, race (variable: race), and Hepatitis C status (variable: rec_hcv_antibody) of patient with ID=493?

  5. What are the mean ages at transplant for male and female recipients? (Hint: consider tab, sum) (Variable: gender 0=Male, 1 = Female).

Part 2#

  1. Generate a variable called age_categories that is 0 for children (ages<18), 1 for adults (18-60), and 2 for senior citizens (>60). What is the mean number of years patients spent on the waitlist in each age group? (Hint: consider tab, sum)

  2. Type the command describe to see a list of all variables. Which ones don’t have a variable label? Write code to give a variable label to all variables that don’t yet have one. Then run describe again to show the labeled variables.

  3. Variable abo represents blood type and is coded as 1=A, 2=B, 3=AB, 4=O. Variable prev represents whether the patient has had a previous transplant and is coded 0=No, 1=Yes. Create a value label for prev. Put the command tab abo prev in your script, to produce the following output (with XXX filled in):

. tab abo prev 

           |    Prev Kidney Tx
       abo |         No       Yes |     Total
-----------+----------------------+----------
       1=A |       XXX        XXX |       XXX 
       2=B |       XXX        XXX |       XXX 
      3=AB |       XXX        XXX |       XXX 
       4=O |       XXX        XXX |       XXX 
-----------+----------------------+----------
     Total |       XXX        XXX |       XXX

.

  1. Generate a new variable called bmi_whocat, representing WHO categories of BMI. BMI category should have the following values: missing if BMI is missing; 1 (labeled “underweight”) if BMI<18.5; 2 (labeled “normal”) if BMI is 18.5-25; 3 (labeled “overweight”) if BMI is 25.1-30; 4 (labeled “obese”) if BMI is 30.1=40. Put the command tab bmi_whocat in your script, to produce the following output (with XXX filled in):

. tab bmi_whocat

 bmi_whocat |      Freq.     Percent        Cum.
------------+-----------------------------------
underweight |        XXX       XX.XX      XX.XX
     normal |        XXX       XX.XX      XX.XX
 overweight |        XXX       XX.XX      XX.XX
      obese |        XXX       XX.XX      XX.XX
------------+-----------------------------------
      Total |      XXX      XX.XX

.

  1. List the ID and age of every patient who is older than 80. List them in order with the oldest patient first.

       XXXX    XX 
       XXXX    XX  
       XXXX    XX  
       XXXX    XX  
       XXXX    XX