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Spillover effects refer to the impact of an intervention on individuals not directly exposed themselves but connected to intervention recipients within the network. In network-based studies, outcomes may be missing due to study termination or participant dropout, termed censoring. We introduce an inverse probability censoring weighted estimator which extends the inverse probability weighted estimator\u00a0for network-based observational studies to handle possible outcome censoring. We prove the consistency and asymptotic normality of the proposed estimator and derive a closed-form estimator for its asymptotic variance. Applying the inverse probability censoring weighted estimator, we assess spillover effects in a network-based study of a nonrandomized intervention with outcome censoring. A simulation study evaluates the finite-sample performance of the inverse probability censoring weighted estimator, demonstrating its effectiveness with sufficiently large sample sizes and number of connected subnetworks. We then employ the method to assess spillover effects of community alerts on self-reported human immunodeficiency virus risk behavior among people who inject drugs and their contacts in the Transmission Reduction Intervention Project (TRIP), from 2013 to 2015, Athens, Greece. Results suggest that community alerts may help reduce human immunodeficiency virus risk behavior for both the individuals who receive them and others in their network, possibly through shared information. In this study, we found that the risk of human immunodeficiency virus behavior was reduced by increasing the proportion of a participant\u2019s immediate contacts exposed to community alerts.<\/jats:p>","DOI":"10.1177\/09622802251382586","type":"journal-article","created":{"date-parts":[[2025,10,7]],"date-time":"2025-10-07T17:01:34Z","timestamp":1759856494000},"page":"2284-2301","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["Assessing spillover effects: Handling missing outcomes in network-based studies"],"prefix":"10.1177","volume":"34","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4939-7136","authenticated-orcid":false,"given":"TingFang","family":"Lee","sequence":"first","affiliation":[{"name":"New York University Grossman School of Medicine"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ashley L","family":"Buchanan","sequence":"additional","affiliation":[{"name":"University of Rhode Island"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Natallia","family":"Katenka","sequence":"additional","affiliation":[{"name":"University of Rhode Island"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Laura","family":"Forastiere","sequence":"additional","affiliation":[{"name":"Yale University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"M Elizabeth","family":"Halloran","sequence":"additional","affiliation":[{"name":"University of Washington"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3307-0246","authenticated-orcid":false,"given":"Georgios","family":"Nikolopoulos","sequence":"additional","affiliation":[{"name":"University of Cyprus"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2025,10,7]]},"reference":[{"key":"e_1_3_4_2_2","doi-asserted-by":"publisher","DOI":"10.1198\/016214504000001844"},{"key":"e_1_3_4_3_2","doi-asserted-by":"publisher","DOI":"10.1177\/0962280210395740."},{"key":"e_1_3_4_4_2","doi-asserted-by":"publisher","DOI":"10.1177\/0962280210386779"},{"key":"e_1_3_4_5_2","doi-asserted-by":"publisher","DOI":"10.1198\/016214508000000292"},{"key":"e_1_3_4_6_2","doi-asserted-by":"publisher","DOI":"10.1198\/016214506000000636"},{"key":"e_1_3_4_7_2","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.2020.1768100"},{"key":"e_1_3_4_8_2","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/asw047"},{"key":"e_1_3_4_9_2","doi-asserted-by":"publisher","DOI":"10.1214\/22-AOAS1713"},{"key":"e_1_3_4_10_2","doi-asserted-by":"publisher","DOI":"10.1093\/jrsssc\/qlae008"},{"key":"e_1_3_4_11_2","doi-asserted-by":"publisher","DOI":"10.1515\/jci-2013-0002"},{"key":"e_1_3_4_12_2","doi-asserted-by":"publisher","DOI":"10.1111\/biom.13459"},{"key":"e_1_3_4_13_2","doi-asserted-by":"publisher","DOI":"10.1111\/biom.13125"},{"key":"e_1_3_4_14_2","doi-asserted-by":"publisher","DOI":"10.1214\/16-AOAS1005"},{"key":"e_1_3_4_15_2","unstructured":"Nikolopoulos GK Friedman SR Buchanan AL. Transmission reduction intervention project (TRIP) Athens Greece Site 2013\u20132015. 2024 DOI: 10.3886\/ICPSR39059.v1. Accessed from https:\/\/doi.org\/10.3886\/ICPSR39059.v1."},{"key":"e_1_3_4_16_2","doi-asserted-by":"publisher","DOI":"10.1038\/srep38100"},{"key":"e_1_3_4_17_2","doi-asserted-by":"publisher","DOI":"10.3389\/fmicb.2018.01825"},{"issue":"11","key":"e_1_3_4_18_2","first-page":"2449","article-title":"Assessing individual and disseminated effects in network-randomized studies","volume":"187","author":"Buchanan A","year":"2018","unstructured":"Buchanan A, Vermund S, Friedman S, et al. Assessing individual and disseminated effects in network-randomized studies. Am J Epidemiol 2018; 187(11): 2449\u20132459.","journal-title":"Am J Epidemiol"},{"key":"e_1_3_4_19_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10461-016-1413-y"},{"key":"e_1_3_4_20_2","doi-asserted-by":"crossref","unstructured":"Robins JM Rotnitzky A Scharfstein DO. 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