Skip to main content
. Author manuscript; available in PMC: 2010 Jan 1.
Published in final edited form as: Soc Networks. 2009 Jan;31(1):92–103. doi: 10.1016/j.socnet.2008.10.005

Table 5.

Coefficients from Regression Models Predicting Bridging in Older Adults’ Networks from Closeness to and Frequency of Contact with Network Members, and Network Composition

Predictors Brokerage potential (Negative binomial)a Sole bridge status (Logistic)b
Age (divided by 10) 3.175 (.027) 1.045 (.107)
Female 28.606*** (.040) 1.637** (.269)
African-American .984 (.055) 1.176 (.203)
Latino −10.693 (.110) .878 (.219)
Education (ref = less than high school)
Graduated high school −2.597 (.085) .997 (.197)
Some college 15.916 (.076) 1.209 (.249)
College degree 16.868* (.066) .874 (.168)
Retired −13.488** (.046) .628** (.091)
Marital status (ref = married/partnered)
Separated/divorced 26.239*** (.058) 3.192*** (.579)
Widowed 12.545 (.072) 2.390*** (.421)
Never married 14.546 (.105) 2.616** (.897)
Closeness to network members −12.658* (.053) .615** (.098)
Frequency of interaction w/network members −.384*** (.000) .993*** (.001)
Kin composition −50.218*** (.041) .327*** (.032)
F (d.f.) 98.03*** (14, 36) 26.66*** (15, 35)
*

p < .05,

**

p < .01,

***

p < .001 (two-tailed tests)

a

The total number of pairs of alters in the network is included as the exposure variable. Negative binomial coefficients are transformed to reflect percent change ([(exp b) − 1]100). Standard errors for the original coefficients are in parentheses.

b

Includes control for the number of alter-pairs in the network.