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      Longitudinal analysis of large social networks: Estimating the effect of health traits on changes in friendship ties

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          Abstract

          We develop novel mixed effects models to examine the role of health traits on the status of peoples' close friendship nominations in the Framingham Heart Study. The health traits considered are both mutable (body mass index (BMI), smoking, blood pressure, body proportion, muscularity, and depression) and, for comparison, basically immutable (height, birth order, personality type, only child, and handedness); and the traits have varying degrees of observability. We test the hypotheses that existing ties (i.e. close friendship nominations) are more likely to dissolve between people with dissimilar (mutable and observable) health traits whereas new ties are more likely to form between those with similar (mutable and observable) traits while controlling for persons' age, gender, geographic separation, and education. The mixed effects models contain random effects for both the nominator (ego) and nominated (alter) persons in a tie to account for the fact that people were involved in multiple relationships and contributed observations at multiple exams. Results for BMI support the hypotheses that people of similar BMI are less likely to dissolve existing ties and more likely to form ties, while smoker to non-smoker ties were the least likely to dissolve and smoker to smoker ties were the most likely to form. We also validated previously known findings regarding homophily on age and gender, and found evidence that homophily also depends upon geographic separation. Copyright © 2011 John Wiley & Sons, Ltd.

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          Uncovering individual and collective human dynamics from mobile phone records

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            Social networks and collateral health effects.

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              Interviewer effects in measuring network size using a single name generator

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                Author and article information

                Journal
                Stat Med
                Stat Med
                sim
                Statistics in Medicine
                John Wiley & Sons, Ltd. (Chichester, UK )
                0277-6715
                1097-0258
                30 April 2011
                02 February 2011
                : 30
                : 9
                : 950-964
                Affiliations
                [a ]Department of Health Care Policy, Harvard Medical School 180 Longwood Avenue, Boston, MA 02115, U.S.A.
                [b ]Department of Sociology, Harvard University Cambridge, MA 02140, U.S.A.
                Author notes
                *Correspondence to: A. James O'Malley, Department of Health Care Policy, Harvard Medical School, 180 Longwood Avenue, Boston, MA 02115-5899, U.S.A.
                Article
                10.1002/sim.4190
                3079434
                21287589
                7d6dd004-3cbb-4265-9226-0c2f9ce17fd4
                Copyright © 2011 John Wiley & Sons, Ltd.

                Re-use of this article is permitted in accordance with the Creative Commons Deed, Attribution 2.5, which does not permit commercial exploitation.

                History
                : 01 December 2009
                : 09 December 2010
                Categories
                Research Articles

                Biostatistics
                dyadic independence,hierarchical model,homophily on health traits,longitudinal,social network

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