A Note on Empirical Sample Distribution of Journal Impact Factors in Major Discipline Groups

34 Pages Posted: 16 Feb 2010  

Sudhanshu K. Mishra

North-Eastern Hill University (NEHU)

Multiple version iconThere are 2 versions of this paper

Date Written: February 14, 2010

Abstract

What type of statistical distribution do the Journal Impact Factors follow? In the past, researchers have hypothesized various types of statistical distributions underlying the generation mechanism of journal impact factors. These are: lognormal, normal, approximately normal, Weibull, negative exponential, combination of exponentials, Poisson, Generalized inverse Gaussian-Poisson, negative binomial, generalized Waring, etc. It is pertinent to note that the major characteristics of JIF data lay in the asymmetry and non-mesokurticity. The present study, frequently encounters Burr-XII, inverse Burr-III (Dagum), Johnson SU, and a few other distributions closely related to Burr distributions to best fit the JIF data in subject groups such as biology, chemistry, economics, engineering, physics, psychology and social sciences.

Keywords: Journal impact factor, JIF, Theoretical distribution, Burr, Dagum, Generalized extreme value, generalized gamma, Inverse Gaussian, Johnson SU, Johnson SB, Kumaraswamy, Log-logistic, lognonmal, log-Pearson, Weibull, Generalized normal, Hypersecant, Beta

JEL Classification: C, C4, A14, Z

Suggested Citation

Mishra, Sudhanshu K., A Note on Empirical Sample Distribution of Journal Impact Factors in Major Discipline Groups (February 14, 2010). Available at SSRN: https://ssrn.com/abstract=1552723 or http://dx.doi.org/10.2139/ssrn.1552723

Sudhanshu K. Mishra (Contact Author)

North-Eastern Hill University (NEHU) ( email )

NEHU Campus
Shillong, 793022
India
03642550102 (Phone)

HOME PAGE: http://www.nehu-economics.info

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