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The bibliometric quotient (BQ), or how to measure a researcher’s performance capacity: A Bayesian Poisson Rasch model

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  • Mutz, Rüdiger
  • Daniel, Hans-Dieter

Abstract

Regarding evaluation of individual researchers, the bibliometric indicators approach has been increasingly discussed recently, but there are some problems involved with it: construct definition, measurement errors, level of scale, dimensionality, normalization. Based on a psychometric model, the Rasch model, we developed a measuring scale for the theoretical construct ‘researcher’s performance capacity,’ defined as the competency of a researcher to write influential papers. The aim was a scale that is one-dimensional and continuous, is applicable to bibliometric count variables, and takes measurement errors into account. In this paper we present the psychometric model (Bayesian Poisson Rasch model, BPR) and its assumptions and examine the behavior of the model under various sampling conditions. For a sample of N = 254 researchers in a quantitative methodology section of an undisclosed German academic society for social sciences, using the BPR model we developed a scale that we named ‘Bibliometric Quotient’ (BQ, M = 100, SD = 15) (following the term ‘intelligence quotient’). The scale fulfills most of the test-theoretical requirements (e.g., high reliability αt = .96, no differential item functioning except for academic age and German states) and in addition allows researchers to be ranked. Women’s BQ scores were 8.3 points lower on the scale than men’s BQ scores.

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  • Mutz, Rüdiger & Daniel, Hans-Dieter, 2018. "The bibliometric quotient (BQ), or how to measure a researcher’s performance capacity: A Bayesian Poisson Rasch model," Journal of Informetrics, Elsevier, vol. 12(4), pages 1282-1295.
    • Handle: RePEc:eee:infome:v:12:y:2018:i:4:p:1282-1295
    DOI: 10.1016/j.joi.2018.10.006
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    1. Boris Forthmann, 2023. "Researcher capacity estimation based on the Q model: a generalized linear mixed model perspective," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(8), pages 4753-4764, August.

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