Table 9.

Topology bias regression: beta coefficients from closeness and in-degree simulations.

Variables	Model 1	Model 2	Model 3	Model 4	Model 5	Model 6
	Component size	Bicomponent size	Distance	Transitivity	TauRC	CONCOR
Intercept	.134**	.154*	.025	.274***	.153***	.025***
	(.05)	(.06)	(.02)	(.08)	(.02)	(.01)
Correlation with Centrality	.07**	.051***	.069***	.185***	.014	.023***
	(.03)	(.01)	(.01)	(.06)	(.02)	(.01)
Correlation type (0 = closeness 1 = in-degree)	.016***	.008***	.01***	.009***	.004*	.003***
	(.004)	(.002)	(.002)	(.002)	(.002)	(.001)
Correlation with Centrality*Correlation type	.043***	.009**	.011**	.014***	.012***	.007***
	(.01)	(.003)	(.004)	(.004)	(.003)	(.001)
Directed	−.039*	−.026	−.024**	−.069*	−.011	−.005
	(.02)	(.02)	(.01)	(.03)	(.01)	(.003)
Correlation with Centrality*Directed	−.026**	−.022***	−.019***	−.049*	−.011	−.012***
	(.01)	(.01)	(.004)	(.02)	(.01)	(.003)
Log of Size	−.008	−.006	.019***	−.023	−.005	4e−04
	(.01)	(.01)	(.004)	(.02)	(.005)	(.002)
Correlation with Centrality*Log of Size	−.007	−.004	−.005*	−.018	.002	−.002
	(.01)	(.003)	(.002)	(.01)	(.003)	(.001)
In-degree Std. Dev.	−.001	−.004	−.006***	−.012	3e−04	−1e−04
	(.004)	(.01)	(.002)	(.01)	(.002)	(.001)
Correlation with Centrality*In-degree Std. Dev.	.002	.003*	.002*	−.007	−.002	−4e−04
	(.002)	(.001)	(.001)	(.004)	(.001)	(.001)
N	96	96	96	96	96	96
Networks	12	12	12	12	12	12

Note: The regression uses the beta slopes from each line as the dependent variable. The direction of the bias is ignored when calculating the regressions. The betas represent the expected increase in bias for a 10% increase in the amount of missing data. Larger numbers mean larger bias with more missing data. The correlation with centrality takes four values: −.75, −.25, .25, and .75.