A Statistical Approach to Model the H-Index Based on the Total Number of Citations and the Duration from the Publishing of the First Article

The productivity of researchers and the impact of the work they do are a preoccupation of universities, research funding agencies, and sometimes even researchers themselves. The h-index (h) is the most popular of different metrics to measure these activities. This research deals with presenting a practical approach to model the h-index based on the total number of citations (NC) and the duration from the publishing of the first article (D1). To determine the effect of every factor (NC and D1) on h, we applied a set of simple nonlinear regression. The results indicated that both NC and D1 had a significant effect on h (  < 0.001). Also, the determination of coefficient for this equation to estimate h was 93.6%. Finally, to model and estimate the h-index, as a function of NC and D1, multiple nonlinear quartile regression was used. The goodness of the fitted model was also assessed.