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. 2021 Jun 4;190(11):2442–2452. doi: 10.1093/aje/kwab167

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© The Author(s) 2021. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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Study of Exclusion Criteria in a University Population (eX-FLU) and stochastic-block network simulation results for a hypothetical vaccine according to varying assortativity coefficients. A) eX-FLU network; B) stochastic-block network. From light to dark gray (left to right), results are shown for the traditional model, cluster model, 1-step model, and 2-step model. The y-axis and box plots show the bias, defined as the regression model log-transformed risk ratio (RR) minus the true log-transformed RR. Whiskers indicate the 2.5th and 97.5th percentiles. The z-axis and diamonds show the 95% confidence interval (CI) coverage, defined as the proportion of 95% CIs that contained the true value. The x-axis indicates the value for the assortativity coefficient in expectation. Higher values indicate greater assortativity. , estimated RR for the unit-treatment effect; , true RR for the unit-treatment effect.

Inline graphic — Study of Exclusion Criteria in a University Population (eX-FLU) and stochastic-block network simulation results for a hypothetical vaccine according to varying assortativity coefficients. A) eX-FLU network; B) stochastic-block network. From light to dark gray (left to right), results are shown for the traditional model, cluster model, 1-step model, and 2-step model. The y-axis and box plots show the bias, defined as the regression model log-transformed risk ratio (RR) minus the true log-transformed RR. Whiskers indicate the 2.5th and 97.5th percentiles. The z-axis and diamonds show the 95% confidence interval (CI) coverage, defined as the proportion of 95% CIs that contained the true value. The x-axis indicates the value for the assortativity coefficient in expectation. Higher values indicate greater assortativity. , estimated RR for the unit-treatment effect; , true RR for the unit-treatment effect.