Skip to content
 

Chad on ethics

Chad Heilig is a statistics Ph.D. graduate of Berkeley who has moved from theoretical statistics to work at the CDC. He recently wrote a paper on ethics in statistics that will appear in Clinical Trials. The paper is interesting to read–it presents a historical overview of some ideas about ethics and statistics in medical studies.

Two key ethical dilemmas in clinical trials are:

(1) The conflict between the goal of saving future lives (by learning as much as possible, right away, about effectiveness of treatments), and the goal of treating current patients as effectively as possible (which, in some settings, means using the best available treatment, and in others means using something new–but will not, in general, correspond to random assignment).

(2) The conflict between the goals in (1)–to help current and future patients–and the goals of the researcher, which can include pure scientific knowledge as well as $, glory, etc.

As Chad points out, it’s a challenge to quantify either of these tradeoffs. For example, how many lives will be saved by performing a large randomized trial on some drug, as compared to using it when deemed appropriate and then learning its effectiveness from observational studies. (It’s well known that observational studies can give wrong answers in such settings.)

I completely disagree with the following statement on page 5 of the paper, which Chad attributes to Palmer (1993): “Where individual ethics is favored, one ought to employ Bayesian statistical methods; where collective ethics is favored, frequentist methods apply.” This doesn’t make sense to me. (For one thing, “frequentist methods” is an extremely general class which includes Bayesian methods as a special case.)

For a copy of the paper, email Chad at cqh9@cdc.gov