I’m not the first one to suggest that Biostatistics has been undervalued in the scientific community, and some of the shortcomings of epidemiology and biostatistics have been noted elsewhere. But this previous work focuses primarily on the contributions of statistics/biostatistics at the purely scientific level.
The Cox Proportional Hazards model is one of the most widely used statistical models in the analysis of data from clinical trials and other medical studies. The corresponding paper has been cited over 32,000 times; this is a dramatically low estimate of the number of times the model has been used. It is one of “those methods” that doesn’t even require a reference to the original methods paper anymore.
Many of the most influential medical studies, including major studies like the Women’s Health Initiative have used these methods to answer some of our most pressing medical questions. Despite the incredible impact of this statistical technique on the world of medicine and public health, it has not received the Nobel Prize. This isn’t an aberration, statistical methods are not traditionally considered for Nobel Prizes in Medicine. They primarily focus on biochemical, genetic, or public health discoveries.
In contrast, many economics Nobel Prizes have been awarded primarily for the discovery of a new statistical or mathematical concept. One example is the ARCH model. The Nobel Prize in Economics in 2003 was awarded to Robert Engle, the person who proposed the original ARCH model. The model has gone on to have a major impact on financial analysis, much like the Cox model has had a major impact on medicine?
So why aren’t Nobel Prizes in medicine awarded to statisticians more often? Other methods such as ANOVA, P-values, etc. have also had an incredibly large impact on the way we measure and evaluate medical procedures. Maybe as medicine becomes increasingly driven by data, we will start to see more statisticians recognized for their incredible discoveries and the huge contributions they make to medical research and practice.
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