Does the h index have predictive power?

Abstract

Bibliometric measures of individual scientific achievement are of particular interest if they can be used to predict future achievement. Here we report results of an empirical study of the predictive power of the h index compared with other indicators. Our findings indicate that the h index is better than other indicators considered (total citation count, citations per paper, and total paper count) in predicting future scientific achievement. We discuss reasons for the superiority of the h index.citations ͉ prediction ͉ achievement T he h index of a researcher is the number of papers coauthored by the researcher with at least h citations each (1). We have recently proposed it as a representative measure of individual scientific achievement. Other commonly used bibliometric measures of individual scientific achievement are total number of papers published (N p ) and total number of citations garnered (N c ). Recently, Lehmann et al. (2,3) have argued that the mean number of citations per paper (n c ϭ N c /N p ) is a superior indicator. Here we wish to address the question: which of these four measures is best able to predict future scientific achievement?For the purposes of this article, we do not wish to dwell on the controversial question of what is the optimal definition of scientific achievement.† We are not interested in measuring the past achievement of an individual, e.g., for the purpose of awarding a prize or for election to a prestigious academy, but rather in predicting future achievement. So we could simply bypass this question by defining ''scientific achievement'' by the bibliometric measure under consideration and ask: which measure is better able to predict its future values? For example, how likely is a researcher who today has a large number of citations to gain a large number of citations in future years? To the extent that a bibliometric measure ref lects particular traits of the researcher rather than random events, it should have higher predictive power than another measure that is more dependent on random events. For example, we argued in ref. 1 that the total number of citations, N c , ''may be inf lated by a small number of 'big hits,' which may not be representative of the individual if he/she is coauthor with many others on those papers.'' For that individual, the present N c value is not likely to be a good predictor of his/her future N c values.Alternatively, among the indicators listed in the first paragraph, it may be argued that the total number of citations, N c , is the one that best reflects scientific achievement because it gives a measure of the integrated impact of a scientist's work on the work of others. Then, we would like to know: which indicator is best able to predict N c at a future time? It is certainly not obvious that the answer is N c itself.There are two slightly different questions of interest. (i) Given the value of an indicator at time t 1 , I(t 1 ), how well does it predict the value of itself or of another indicator at a future time t 2 , IЈ(t 2 )? This quest...

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