The h index research output measurement: Two approaches to enhance its accuracy

The h index is a widely used indicator to quantify an individual's scientific research output. But it has been criticized for its insufficient accuracy—the ability to discriminate reliably between meaningful amounts of research output. As a single measure it cannot capture the complete information on the citation distribution over a scientist's publication list. An extensive data set with bibliometric data on scientists working in the field of molecular biology is taken as an example to introduce two approaches providing additional information to the h index: (1) h2 lower, h2 center, and h2 upper are proposed, which allow quantification of three areas within a scientist's citation distribution: the low impact area (h2 lower), the area captured by the h index (h2 center), and the area of publications with the highest visibility (h2 upper). (2) Given the existence of different areas in the citation distribution, the segmented regression model (sRM) is proposed as a method to statistically estimate the number of papers in a scientist's publication list with the highest visibility. However, such sRM values should be compared across individuals with great care.