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A guide for choosing community detection algorithms in social network studies: The Question-Alignment approach

CITE Title : A guide for choosing community detection algorithms in social network studies: The Question-Alignment approach Personal Author(s) : Smith, Natalie R;Zivich, Paul N;Frerichs, Leah;Moody, James;Aiello, Allison E; Published Date : 10 2020;10-2020; Source : Am J Prev Med. 59(4):597-605 URL : https://stacks.cdc.gov/view/cdc/94042 Smith, Natalie R et al. (2020). A guide for choosing community detection algorithms in social network studies: The Question-Alignment approach. 59(4). Smith, Natalie R et al. "A guide for choosing community detection algorithms in social network studies: The Question-Alignment approach" 59, no. 4 (2020) Smith, Natalie R et al. "A guide for choosing community detection algorithms in social network studies: The Question-Alignment approach" vol. 59, no. 4, 2020 Export RIS Citation Information.

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Smith, Natalie R ;

Zivich, Paul N

10 2020 | Am J Prev Med. 59(4):597-605

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Introduction:Community detection, the process of identifying subgroups of highly connected individuals within a network, is an aspect of social networ...
Targeted maximum likelihood estimation of causal effects with interference: a simulation study

CITE Title : Targeted maximum likelihood estimation of causal effects with interference: a simulation study Personal Author(s) : Zivich, Paul N;Hudgens, Michael G;Brookhart, M Alan;Moody, James;Weber, David J;Aiello, Allison E; Published Date : 10 15 2022;10-15-; Source : Stat Med. 41(23):4554-4577 URL : https://stacks.cdc.gov/view/cdc/121532 Zivich, Paul N et al. (2022). Targeted maximum likelihood estimation of causal effects with interference: a simulation study. 41(23). Zivich, Paul N et al. "Targeted maximum likelihood estimation of causal effects with interference: a simulation study" 41, no. 23 (2022) Zivich, Paul N et al. "Targeted maximum likelihood estimation of causal effects with interference: a simulation study" vol. 41, no. 23, 2022 Export RIS Citation Information.

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Zivich, Paul N ;

Hudgens, Michael G

10 15 2022 | Stat Med. 41(23):4554-4577

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Interference, the dependency of an individual's potential outcome on the exposure of other individuals, is a common occurrence in medicine and public ...
Assessing Intervention Effects in a Randomized Trial within a Social Network

CITE Title : Assessing Intervention Effects in a Randomized Trial within a Social Network Personal Author(s) : Alexandria, Shaina J.;Hudgens, Michael G.;Aiello, Allison E.; Published Date : 6 2023;6-2023; Source : Biometrics. 79(2):1409-1419 URL : https://stacks.cdc.gov/view/cdc/117910 Alexandria, Shaina J. et al. (2023). Assessing Intervention Effects in a Randomized Trial within a Social Network. 79(2). Alexandria, Shaina J. and Hudgens, Michael G. and Aiello, Allison E. "Assessing Intervention Effects in a Randomized Trial within a Social Network" 79, no. 2 (2023) Alexandria, Shaina J. et al. "Assessing Intervention Effects in a Randomized Trial within a Social Network" vol. 79, no. 2, 2023 Export RIS Citation Information.

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Alexandria, Shaina J. ;

Hudgens, Michael G.

6 2023 | Biometrics. 79(2):1409-1419

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Studies of social networks provide unique opportunities to assess the causal effects of interventions that may impact more of the population than just...