Regression for citation data: An evaluation of different methods

作者：

Highlights：

• Ordinary least squares regression is recommended for citation data +1 after a logistic transformation.

• The generalised linear model with lognormal residuals is recommended for citation data.

• Inappropriate regression models can substantially inflate the chance of detecting false factors within citation data.

• Regression models are evaluated for citation data and clear recommendations made for the best ones.

摘要

•Ordinary least squares regression is recommended for citation data +1 after a logistic transformation.•The generalised linear model with lognormal residuals is recommended for citation data.•Inappropriate regression models can substantially inflate the chance of detecting false factors within citation data.•Regression models are evaluated for citation data and clear recommendations made for the best ones.

论文关键词：Informetrics,Altmetrics,Citation distributions,Lognormal,Powerlaw,Regression

论文评审过程：Received 2 July 2014, Revised 26 September 2014, Accepted 30 September 2014, Available online 22 October 2014.

论文官网地址：https://doi.org/10.1016/j.joi.2014.09.011