2017/04/07 by Robin Haunschild, Lutz Bornmann, Haunschild, Robin +1
Agricultural and Biological Sciences · Computer Science · Economics, Econometrics and Finance · #Data Management and Algorithms #Digital Libraries (cs.DL) #FOS: Computer and information sciences #Sensory Analysis and Statistical Methods #Spatial and Panel Data Analysis
paper · pdf · doi:10.48550/arxiv.1704.02211
openalex publication_date 2017/04/07 · openalex created_date 2022/09/01 · openalex updated_date 2026/07/28
Recently, two new indicators (Equalized Mean-based Normalized Proportion\nCited, EMNPC, and Mean-based Normalized Proportion Cited, MNPC) were proposed\nwhich are intended for sparse data. We propose a third indicator\n(Mantel-Haenszel quotient, MHq) belonging to the same indicator family. The MHq\nis based on the MH analysis - an established method for polling the data from\nmultiple 2x2 contingency tables based on different subgroups. We test (using\ncitations and assessments by peers) if the three indicators can distinguish\nbetween different quality levels as defined on the basis of the assessments by\npeers (convergent validity). We find that the indicator MHq is able to\ndistinguish between the quality levels in most cases while MNPC and EMNPC are\nnot.\n