Measuring the robustness of the journal h-index with respect to publication and citation values: A Bayesian sensitivity analysis. Issue 3 (August 2016) - Malesios, C.
Highlights: In the current paper an accurate measurement of the robustness of the h -index for journals is performed. In doing this a novel sensitivity analysis methodology is employed. Several mathematical models proposed for the h -index are utilized. The estimates from fit of the models were utilized for testing scenarios associated with varying the input parameters of publications ( P ) and citations ( C ). Results derived assist in gaining insight on how a specific journal's h -index varies according to changes in number of P and C . Abstract: Braun, Glänzel, and Schubert (2006) recommended using the h -index as an alternative to the journal impact factor (IF) to qualify journals. In this paper, a Bayesian-based sensitivity analysis is performed with the aid of mathematical models to examine the behavior of the journal h -index to changes in the publication/citation counts of journals. Sensitivity of the h -index was most apparent for changes in the number of citations, revealing similar patterns of behavior for almost all models and independently to the field of research. In general, the h -index was found to be robust to changes in citations up to approximately the 25th percentile of the citation distribution, inflating its value afterwards.