
Abstract Result replicability has often been confused with significance testing because of a misinformed view that statistical significance evaluates result importance and result replicability. Several alternatives, of which the jackknife statistic is one, provide researchers with the tools for estimating result replicability. In the present study, an available data set from A. L. Edwards (1985, p. 57) is used to illustrate the use of the jackknife statistic to assess the replicability of multiple regression results in a concrete fashion. The jackknifed coefficients are computed to assess the stability of beta weights and the multiple R 2 value. Confidence intervals and t statistics are also calculated to facilitate the interpretation of these jackknifed coefficients.
| citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 18 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
