What are the most important problems in biostatistics?
After reading the “You and Your Research” speech by Richard Hamming, I have been asking myself, “What are the important problems in biostatistics?”
After a few minutes, I have come up with the following list:
- Integrating Bayesian and Frequentist methodology
- Statistical methods that: (1) require little computation time; (2) need little memory; or (3) both
- Causal inference in both observational studies and clinical trials
- Fisherian vs. Neyman-Pearson inference
- Reproducible research
The thought also occurred to me: do we really have big problems? I view a huge part of biostatistics as the nuts and bolts of answering big questions in medicine and public health. We don’t necessarily have to have big problems of our own to help solve big problems.
Edit. Here is a stackexchange forum on this question for statistics: http://stats.stackexchange.com/questions/2379/what-are-the-big-problems-in-statistics