Institutional bibliometric analyses compare as a rule the performance of different institutions. The purpose of this paper is to use a statistical approach which not only allows a comparison of the citation impact of papers from selected institutions, but also a comparison of the citation impact of the papers of these institutions with all other papers published in a particular time frame.
The study is based on a randomly selected cluster sample (n=4,327,013 articles and reviews from 2000 to 2004), which is drawn from a bibliometric in-house database including Web of Science data. Regression models are used to analyze citation impact scores. Subsequent to the models, average predictions at specific interesting values are calculated to analyze which factors could have an effect on the impact scores-the journal impact factor (JIF), of the journals which published the papers and the number of affiliations given in a paper.
Three anonymous German institutions are compared with one another and with the set of all other papers in the time frame. As an indicator of institutional performance, fractionally counted PPtop 50% on the level of individual papers are used. This indicator is a normalized impact score whereas each paper is fractionally assigned to the 50 percent most frequently cited papers within its subject category and publication year. The results show that the JIF and the number of affiliations have a statistically significant effect on the institutional performance.
Fractional regression models are introduced to analyze the fractionally counted PPtop 50% on the level of individual papers.
