Table 3.

General linear mixed models for allogrooming network metrics.

GLM with Bootstrap for estimates of fixed effects on allogrooming network
Network metrics	Factor	Estimate	Standard error	p
Eigenvector	Intercept	-0.230	0.085	0.015
	Gender	0.231	0.045	0.001
	Age	-0.014	0.003	0.002
	Matriline	0.003	0.004	0.404
	Hierarchy	0.004	0.003	0.122
Clustering	Intercept	-0.007	0.607	0.990
	Gender	0.681	0.321	0.056
	Age	-0.035	0.032	0.362
	Matriline	0.061	0.045	0.206
	Hierarchy	-0.009	0.027	0.734
Degree	Intercept	-12.075	26.373	0.638
	Gender	71.708	14.753	0.001
	Age	-5.625	0.947	0.000
	Matriline	1.210	1.675	0.457
	Hierarchy	0.393	0.840	0.624
Outdegree	Intercept	37.450	12.688	0.007
	Gender	32.018	7.777	0.004
	Age	-3.560	0.475	0.000
	Matriline	0.524	0.907	0.545
	Hierarchy	-0.973	0.425	0.027
Indegree	Intercept	-49.525	18.027	0.011
	Gender	39.691	8.388	0.001
	Age	-2.064	0.518	0.002
	Matriline	0.686	0.931	0.437
	Hierarchy	1.366	0.522	0.012

In bold, significant attributes.