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. (1st March 2021) - Mahmoudi, Mohammad Reza; Rahmati, Marzieh; Mansor, Zulkefli; Mosavi, Amirhosein; Band, Shahab S.
Abstract : 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 ( N C ) and the duration from the publishing of the first article ( D 1 ). To determine the effect of every factor ( N C and D 1 ) on h, we applied a set of simple nonlinear regression. The results indicated that both N C and D 1 had a significant effect on h (p < 0.001). The determination of coefficient for these equations to estimate the h -index was 93.4% and 39.8%, respectively, which verified that the model based on N C had a better fit. Then, to record the simultaneous effects of N C and D 1 on h, multiple nonlinear regression was applied. The results indicated that N C and D 1 had a significant effect on h (p < 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 N C and D 1, multiple nonlinear quartile regression was used. The goodness of the fitted model was also assessed.