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How Do They ‘End Up Together’? A Social Network Analysis of Self-Control, Homophily, and Adolescent Relationships

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Abstract

Self-control theory (Gottfredson and Hirschi 1990) argues that individuals with similar attributes tend to ‘end up together’ (i.e., homophily) because of the tendency to select friends based on self-control. Studies documenting homophily in peer groups interpret the correlation between self-control, peer delinquency, and self-reported delinquency as evidence that self-control is an influential factor in friendship formation. However, past studies are limited because they do not directly test the hypothesis that self-control influences friendship selection, nor do they account for other mechanisms that may influence decisions. As a result, it is unclear whether the correlation between individual and peer behavior is the result of selection based on self-control or alternative mechanisms. To address this gap in the literature this study employs exponential random graph modeling to test hypotheses derived from self-control theory using approximately 63,000 respondents from 59 schools from the National Longitudinal Survey of Adolescent Health (Add Health). In contrast to the predictions made by Gottfredson and Hirschi (1990), and the conclusions drawn from prior research, there is little evidence that self-control influences friendship selection. The findings are embedded in past work on the relationship between self-control and peer relationships, and implications for future research are discussed.

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Notes

  1. Though not a common nomenclature in the criminological literature, selective mixing characterizes the process of friendship formation implicit in the social causation model of crime and delinquency (see Wright et al. 1999).

  2. Gottfredson and Hirschi (1990) also argue that the relationship between peer and individual behavior can partially be explained as an artifact of self-report measures. Research supporting this argument is discussed briefly below, but not in detail here as this is a separate mechanism generating the relationship between peer and individual behavior (i.e., measurement error).

  3. A separate question, which is often found in research on mediating effects, focuses on whether there is a moderating relationship between self-control and peer delinquency on self-reported delinquency. These studies investigate whether the effect of self-control on delinquency depends on peer delinquency or whether the effect of peer delinquency on delinquency depends on self-control, often referred to as social amplification effects (Wright et al. 2001). Unlike research on mediating effects, research on social amplification is less consistent. Several studies find social amplification effects (Gibson and Wright 2001; Wright et al. 2001; Ousey and Wilcox 2007, cf. Doherty 2006), while others, using more accurate measures of peer delinquency, have found opposite (Meldrum et al. 2009) or null effects (McGloin and Shermer 2009). These mixed findings indicate that the moderating effects of self-control and peer delinquency on delinquency are not well understood.

  4. Preliminary analyses included a variable recording the race/ethnicity of the respondent since race/ethnicity has been shown to be an important predictor of friendship formation (see Moody 1999). This variable was created for non-Hispanic white, African-American, Hispanic, Native American and Asian respondents. Since fewer than half of the 59 schools contained sufficient variation in race for analysis, it was not possible to estimate the effects of race across all the schools. Using the schools with sufficient variability, models including dummy variables for race produce results that are substantively similar to the results presented below. They are excluded here due to space constraints. Full models are available by request from the author.

  5. Students who were not nominated by respondents or who were not included in the sample due to absence on the days in which the survey was conducted create a separate problem. Unless these cases are missing completely at random (Rubin, 1976), inference about the network may be biased due to a non-random mechanism as they are unobserved in the observed data matrix, s. Schools with the highest response rates were included in this analysis due to this problem. Note, however, that this situation is not unique to relational data. Inference about the social network may be biased, but so will inference about individual covariates under a separate modeling framework. As with any study dealing with missing data, assumptions are made to facilitate statistical inference when the problem cannot be addressed by the model. The assumption made in this model is that these cases are missing completely at random.

  6. The coefficients are the Markov chain Monte Carlo estimates. Post estimation inspection of the chains show sufficient mixing and convergence. All non-zero coefficients are significantly different from zero at the 0.001 level.

  7. The visual difference in the plots for the observed network between Figs. 2 and 5 is caused by differences in the limits on the y-axis for each plot. The same network is analyzed and displayed in each figure.

  8. The complete saturated sample contains 3,702 respondents in 16 schools. However, one school containing 44 respondents is excluded from the analysis due to insufficient network data for conducting meaningful analyses. This school does not appear to be significantly different from the schools analyzed. Compared to the saturated sample, the other schools in the Wave I in-home survey used a different question to measure peer data: respondents could nominate 1 male and 1 female friend. The sample of the social network in each school is substantially limited as a result.

  9. The influence of school characteristics requires an estimation of a hierarchical model testing the presence of a random effect for self-control and exploring cross-level interactions. Unfortunately, hierarchical models for ERG models are not available. Running models for each school and then investigating the dispersion of the effects of self-control (the approach used here) offers a crude means of approximating the distribution for the self-control parameter. However, the finding that there is little variability in the effect across schools suggests that this approximation is not entirely inadequate for the problem at hand.

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  1. Department of Sociology, University of Washington, Savery Hall, Box 353340, Seattle, WA, 98195-3340, USA

    Jacob T. N. Young

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Appendix A

Appendix A

See Table 2.

Table 2 Means and standard deviations for variables by school (N = 59)
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Young, J.T.N. How Do They ‘End Up Together’? A Social Network Analysis of Self-Control, Homophily, and Adolescent Relationships. J Quant Criminol 27, 251–273 (2011). https://doi.org/10.1007/s10940-010-9105-7

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