Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
Recently, Cohen and Gujarati [2] have suggested that when multicollinearity is present there is “ …danger involved in mechanically dropping variables from multiple regression equations by t tests because t values of the regression coefficients may not be significantly different from zero when the true (population) values of these coefficients are in fact not zero…” The problem they discuss is not a new one and has been extensively treated in the existing literature. However, their approach is straightforward and will certainly aid the practitioner in his understanding of the problems associated with multicollinearity.