Table 5.

GLMMs examining the effects of an interaction between females’ dominance rank and period of study on the outcome of their normalized David’s scores (i.e., hierarchy steepness), allogrooming social network degree (i.e., rank-related skew in degree) and allogrooming network eigenvector (i.e., rank-related skew in eigenvector), for macaque groups that experienced a successful male introduction.

	β	SE	t	p r(>|t|)	p perm
Outcome: Normalized David’s scores
(Intercept)	8.56	0.36	23.53	<0.01**
Period (post- vs pre-introduction)	−1.35	0.51	2.62	0.11
Rank (Post-introduction)	−0.32	0.01	−26.89	<0.01**
Rank (Pre-introduction)	−0.50	0.01	−42.58	<0.01**
Introductions: Rank	−0.19	0.02	−11.10	<0.01**
Outcome: Allogrooming degree
(Intercept)	0.45	0.16	2.72	0.04*
Period (post- vs pre-introduction)	0.04	0.21	0.17	0.87
Rank (Post-introduction)	0.31	0.14	2.23	0.03*	0.04*
Rank (Pre-introduction)	0.57	0.14	4.04	<0.01**	<0.01**
Age	0.00	0.01	0.00	1.00
Relatedness coefficient	−0.11	0.17	−0.65	0.52
Introductions: Rank	0.25	0.19	1.30	0.20
Outcome: Allogrooming eigenvector
(Intercept)	0.24	0.02	11.17	<0.01**
Period (post- vs pre-introduction)	0.03	0.02	1.51	0.14
Rank (Post-introduction)	0.05	0.03	1.84	0.07(*)	0.05*
Rank (Pre-introduction)	0.11	0.03	4.19	<0.01**	<0.01**
Age	0.00	0.00	0.28	0.78
Relatedness coefficient	−0.01	0.03	−0.31	0.76
Introductions: Rank	0.06	0.04	1.69	0.10

In each model, we included a 3-level nested random effect of categorical ‘group size’ (level-3), ‘group ID’ (level-2), and ‘year of observation’ (level-1). For models on allogrooming degree and eigenvector, p_perm represents p values calculated based on comparing observed model coefficients with coefficients generated based on network measures calculated from 1000 permuted networks generated from post-network ‘node-swapping’ randomizations.

^*p < 0.05;

^**p < 0.01;

^(*)0.05 < p < 0.10.