A widely quoted statistic is that it takes 17 years for research to find it’s way from the initial discovery to clinical practice. That statistic has always bothered me. How do you know that it takes this long? How could you measure such a thing? Wouldn’t it depend on the type of discovery? Apparently, I’m not the only one bothered by this statistic. The authors of this research paper looked at all the publications that purported to estimate the time lag between discovery and clinical adoption. They found that different authors used different markers for the date of discovery and the date of clinical adoption. Furthermore, reporting is poor, with little discussion of the variation in the estimated time lag. Continue reading

# Monthly Archives: January 2015

# Recommended: Tessera. Open source environment for deep analysis of large complex data

I have not had time to preview this software, but it looks very interesting, It takes large problems and converts them to a form for parallel processing, not by changing the underlying algorithm, which would be very messy, but by splitting the data into subsets, analyzing each subset, and recombining these results. Such a method “Divide and Recombine” should work well for some analysis, but perhaps not so well for others. It is based on the R programming language. If I get a chance to work with this software, I’ll let you know what I think. Continue reading

# Recommended: Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD Statement

If you are writing up a paper that uses a complex regression model (complex meaning multiple independent variables), you need to document information that allows the reader to assess the quality of the predictions that your model would produce. This paper provides a checklist of things that you need to document in such a paper, and is an extension of the CONSORT guidelines to this particular type of research. Continue reading

# PMean: Analyzing ordinal salary categories

Dear Professor Mean,

I have three variables: physicians (%), dentists (%), and salary categories. I want to know if there is a difference in the percentage of physicians and dentists in each salary category. What test I need to use? ANOVA is not appropriate because the outcome is not continuous. Continue reading