Biostatistics Faculty and NIH Awards at U.S. Medical Schools.

The number of biostatistics faculty is positively associated with the amount of NIH research awards in medical schools in the U.S.  (Am Stat. 2015 Feb;69(1):34-40.)

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Plastic Surgery Residents' Understanding and Attitudes Toward Biostatistics: A National Survey.

This study found that plastic surgery residents felt that knowledge of biostatistics was important, however upon objective testing they only had a fair understanding of statistical principles. The residents had difficulty with study study design, ANOVA, regression, and identification of a statistically significant result. Confidence was not a good predictor of objective performance.  (Ann Plast Surg. 2015 Jan 30.)

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Bonferroni multiple comparison test

When performing multiple tests of significance upon a single dataset, there is an ever increasing chance that at least one of these tests will be statistically significant. For example, a p-value of 0.05 means there is a 1-in-20 likelihood of the statistical result occurring by chance alone.  If we perform 20 such tests, then there is a 1-in-1 likelihood of at least one result having a p-value of 0.05 or less.

The Bonferroni correction is simple. When multiple tests of significance are performed, then the cutoff p-value for statistical significance is set to equal 0.05 divided by the number of tests performed.

For example, if 10 tests of significance are performed, the cutoff p-value for statistical significance would be 0.05 / 10 = 0.005 when using the Bonferroni correction. If 5 tests are performed, then the cutoff p-value would be 0.05 / 5 = 0.01.

Recommended Books to Help You Prepare for the USMLE Biostatistics Section

The USMLE, as well as board certification examinations, almost all contain questions on basic statistics. A good review of biostatistics thus is helpful for both physicians in training and practicing physicians. As a teacher of bioastatistics for medical students, I've had the opportunity to review a large number of biostatistic review guides, and as a researcher frequently use several references which are helpful for the physician interested in more in-depth learning.

• First Aid for the USMLE Step 1. This review has a nice, short section on biostatistics that covers most of the basics. You don't need to get the latest version of this book, obviously, because the basic concepts of biostatistics doesn't change.
• High-Yield Biostatistics. This is a very well written book, which addresses biostatistics, epidemiology, and public health with the USMLE Step 1 exam in mind. This contains more in-depth information on biostatistics than most people will require or want, but it is a good reference and highly recommended.
• PDQ Statistics. This small book covers biostatistics with the researcher in mind. It has good chapter summaries, and especially good pitfalls to watch out for when performing statistics or reading the medical literature.
• How to Lie with Statistics. Required reading for all physicians.
• Basic and Clinical Biostatistics. This is a fantastic reference book. It covers the topic too extensively to be used as a quick review guide, however, it is an excellent reference that physicians engaged in research should have on their bookshelf.