hw1

hw1#

Overview & video

Write a .do file which imports data from hw1.txt and performs the tasks described below. Name it hw1.lastname.firstname.do and it should create a log file called hw1.lastname.firstname.log. Your .do file should follow conventions for .do file structure described in class: session pwd. Make sure your log file displays only the output of interest. But do not submit your log files as part of the assignment.

Evaluation will be based on the log file produced when we run your script on our machines. Please follow the coding guidelines from class including structure, indentation, and annotation.

Codebook

Variable	Description	Values
transplants.dta
`fake_id`	Patient ID	Numeric
`bmi`	Body mass index (kg/m2)	Numeric
`dx`	Primary diagnosis	String (see dataset)
`init_age`	Age	Numeric
`prev`	History of previous transplant	0=No / 1=Yes
`peak_pra`	Peak PRA	Numeric
`female`	Sex	0=No / 1=Yes
`received_kt`	Patient eventually received a kidney transplant?	0=No / 1=Yes

This dataset contains simulated data on registrants for the deceased donor kidney waitlist.

Questions

Question 1. Print the following sentence: Question 1: There are xxxx records in the dataset. The xxxx should be replaced with the actual number of records in the dataset.

Question 2. Print the following sentence: Question 2: The median [IQR] age is XX [XX-XX] among males and XX [XX-XX] among females. IQR stands for interquartile range. The XX values should be replaced with correct values, rounded to the nearest whole number (for example, 47). Ignore missing values; that is, calculate median [IQR] only using the non-missing values.

Question 3. Print the following sentence: Question 3: XX.X% among males and XX.X% among females have history of previous transplant. The XX.X% values should be replaced with correct percentage values, with one decimal value to the right of the decimal place (for example, 10.5%).

Question 4. Create a new numeric variable named htn, which takes a value of 1 if the variable dx has a value of 4=Hypertensive, and 0 otherwise. This variable should have value labels, Yes for 1 and No for 0. (Hint: what is the data type of this new variable? Is it a numeric or a string?) Run tab htn in your assignment do-file so that it would print the following result.

        htn |       Freq.       Percent       Cum.
------------+-------------------------------------
         No |       XXXX        XXXX          XXXX
        Yes |       XXXX        XXXX          XXXX
------------+-------------------------------------
      Total |       XXXX        XXXX

Question 5. Now you have all the skills to create your first automated Table 1! Write a program called question5 that prints the following table (including Question 5 in the header). The XX values should be replaced with correct values found in the dataset, and should be rounded to the nearest whole number for age and to one decimal place to the right of the decimal point for other variables. Make sure the summary statistics are vertically aligned and justified along the left margin. Run your program and display the table.

Question 5                Males (N=XX)        Females (N=XX)
Age, median (IQR)         XX (XX-XX)          XX (XX-XX)
Previous transplant, %    XX.X%               XX.X%
Cause of ESRD:
Glomerular, %             XX.X%               XX.X%
Diabetes, %               XX.X%               XX.X%
PKD, %                    XX.X%               XX.X%
Hypertensive, %           XX.X%               XX.X%
Renovascular, %           XX.X%               XX.X%
Congenital, %             XX.X%               XX.X%
Tubulo, %                 XX.X%               XX.X%
Neoplasm, %               XX.X%               XX.X%
Other, %                  XX.X%               XX.X%

Hint 1: Use quietly {} and noisily to display the lines nicely without interruptions.

Hint 2: init_age has some missing values. Exclude observations with missing init_age only when calculating the median [IQR] of init_age, but not when calculating the proportion with previous transplants.

Hint 3: some techniques taught in lecture 3 may be helpful for completing this table. You are welcome Lecture 3 techniques if you like, but they are not required.

Question 6. Your research group is investigating demographic characteristics associated with receiving a kidney transplant for waitlisted patients. You run a logistic regression using the following command:

logistic received_kt init_age female

Print a summary table as shown below, with odds ratios (OR) and 95% confidence intervals (CI). The XXXX values should be replaced with the actual values found in the dataset, and should be displayed with two decimal places to the right of the decimal point.

Question 6
Variable         OR    (95% CI)
Age              X.XX  (X.XX-X.XX)
Female           X.XX  (X.XX-X.XX)

Hint: If you like, you may these expressions below after logistic regression to obtain the odds ratio and 95% CI. We will use init_age as an example.

Parameters	Expressions
Odds ratio	`exp(_b[init_age])`
Lower bound of 95% CI	`exp(_b[init_age]+invnormal(0.025) * _se[init_age])`
Upper bound of 95% CI	`exp(_b[init_age]+invnormal(0.975) * _se[init_age])`

Question 7. The logistic regression you ran in Question 6 may not include all observations in the study dataset. Stata drops observations that have missing values in any of the variables included in the regression.

Using the regression results from Question 6, print the following text: Question 7: This regression included XXXX observations whereas the study dataset has XXXX observations in total. Replace XXXX with correct values.

Hint: use one of the e-class scalars. We talked about e-class scalars in Lecture 2.

Question 8. Print the following text: Question 8: I estimate that it took me XXXX hours to complete this assignment. For example, if it took you six hours, your .do file will contain the line

disp "Question 8: I estimate that it took me 6 hours to complete this assignment."

Give an honest answer; this is just for our data collection purposes. Everyone who answers this question will receive full credit for this question. However, this question is worth some points, so don’t skip it!