Lab 9: ❤️ Heart Transplant

Pobability and Statistics

Important

Deadline: 29.03.2025, 23:59. No late submissions will be accepted.

Input

Today, we will be working with data from The Stanford University Heart Transplant Study.

The Stanford University Heart Transplant Study was conducted to determine whether an experimental heart transplant program increased lifespan. Each patient entering the program was designated an official heart transplant candidate, meaning that they were gravely ill and would most likely benefit from a new heart. Some patients got a transplant and some did not. The variable transplant indicates which group the patients were in; patients in the treatment group got a transplant and those in the control group did not. Of the 34 patients in the control group, 30 died. Of the 69 people in the treatment group, 45 died. Another variable called survived was used to indicate whether the patient was alive at the end of the study1.

The data dictionary is as follows:

Variable Description
id ID number of the patient
outcome Survival status with levels alive and deceased
transplant Transplant group with levels control (did not receive a transplant) and treatment (received a transplant)
age Age of the patient at the beginning of the study
survtime Number of days patients were alive after the date they were determined to be a candidate for a heart transplant until the termination date of the study
acceptyear Year of acceptance as a heart transplant candidate
prior Whether or not the patient had prior surgery with levels yes and no
wait Waiting time for transplant

Task

  1. Load the data and review its structure.
  2. Build visualizations to explore the data.
  3. Specify the null and alternative hypotheses to use bootstrap methods to test the hypothesis.
Note

You can use any test statistic you find appropriate for the task. If you use a standard metrics (e.g., mean, proportion etc.), please provide a comparative analysis of the results of bootstrap method and common test (p-values, confidence intervals, etc.).

  1. Interpret the results of the hypothesis test in the context of the assignment.
  2. Provide a conclusion based on the results of the hypothesis test.

Footnotes

  1. Turnbull, Bruce W., Byron Wm. Brown, and Marie Hu. 1974. “Survivorship Analysis of Heart Transplant Data.” Journal of the American Statistical Association 69 (345): 74–80. https://doi.org/10.1080/01621459.1974.10480130.↩︎