Measuring the steepness of a dominance hierarchy is important for classifying a social system in a continuum
between egalitarian and despotic. For this, often the steepness-slope from de Vries et al. (Animal
Behaviour, 2006, 71, 585e592) is often used. It compares the cardinal and ordinal dominance rank of each
individual using the slope of the linear regression. The disadvantage of this measure is that the slope becomes
lower the higher the proportion of unknown relationships (dyads without interactions). In the
present paper, weinvestigatewhat causes this bias, and propose a solution. (1)We show that the bias is due
to the treatment of unknown relationships by the dominance index currently used in this methodology, the
David's score (namely by assuming, among other things, an equal number of wins and losses for both
members of the pair). (2) Instead, using the Average Dominance Index (the average proportion of wins by
each individual from all its opponents) reduces the bias due to unknown relationships, because it excludes
these relationships, and (3) the standard error of the steepness-slope based on the Average Dominance
Index is smaller. (4) The two indices (David's score and Average Dominance Index) result in similar
steepness-slopes when all relationships are known. To compare the two indices we use empirical data
(from four group-years of wild vervet monkeys, Chlorocebus pygerythrus) and data from a computational
model on dominance interactions in a group (DomWorld).We conclude that the AverageDominance Index
(compared to the David's score) is preferable for measuring the steepness-slope.