Abstract
A theoretical model for the distribution of authorships is developed. This model, the shifted Waring distribution, and 15 other discrete probability models are tested for goodness-of-fit against 94 data sets collected from six fields (engineering sciences, medical sciences, physical sciences, mathematical sciences, social sciences, and humanities). The shifted inverse Gaussian-Poisson is found to provide the best fitting. It is suggested that the latter model can be used in the estimation of the number of entries in an author index and in determining the maximum number of authors per paper to be included in an author index. © 1991 John Wiley & Sons, Inc.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Journal of the American Society for Information Science
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
