This blog grew out of a need to separate my professional blogging from personal blogging. With the public trust in clinical trials waning in the wake of Vioxx and Ketek, there is a need for public information and transparency on how clinical trials are conducted. While more information won't solve all of the problems -- this requires a commitment on the part of drug and research companies as well -- I do find that a lot of mistrust stems from a simple misunderstanding of the scientific process in general and how drugs are studied in particular.
Most other blogging on this subject seems to come from doctors. I've found very few statistical bloggers, and I'm the only person I know of that is blogging with a purely biostatistical focus. Yet it is the biostatistician who has to determine whether a clinical trial can give a statistically valid answer, and the doctor or pharmacologist who decides if the statistically valid answer has any meaning or relevance. This blog is about clinical trials and other research, and how to extract conclusions from them.
The material in this blog will draw from the news, my own personal experience, and even a bit of research, and is intended for a general and professional audience.
As for the title: in statistics a "realization" is one instance of data. We dream up these statistical models, use mathematics to say what we can about them without looking at real data, and then examine realizations to see how well our models and methods work in practice. The data that comes out of a clinical trial can be said to be a realization.
