{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T07:03:22Z","timestamp":1788246202672,"version":"build-2803163510"},"reference-count":35,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2024,4,8]],"date-time":"2024-04-08T00:00:00Z","timestamp":1712534400000},"content-version":"vor","delay-in-days":7,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100009480","name":"Stichting Vrienden van het Sophia","doi-asserted-by":"publisher","award":["WAR21\u201072"],"award-info":[{"award-number":["WAR21\u201072"]}],"id":[{"id":"10.13039\/501100009480","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Human Brain Mapping"],"published-print":{"date-parts":[[2024,4]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    The goal of this study was to examine what happens to established associations between attention deficit hyperactivity disorder (ADHD) symptoms and cortical surface and thickness regions once we apply inverse probability of censoring weighting (IPCW) to address potential selection bias. Moreover, we illustrate how different factors that predict participation contribute to potential selection bias. Participants were 9\u2010 to 11\u2010year\u2010old children from the Generation R study (\n                    <jats:italic>N<\/jats:italic>\n                    \u2009=\u20092707). Cortical area and thickness were measured with magnetic resonance imaging (MRI) and ADHD symptoms with the Child Behavior Checklist. We examined how associations between ADHD symptoms and brain morphology change when we weight our sample back to either follow\u2010up (ages 9\u201311), baseline (cohort at birth), or eligible (population of Rotterdam at time of recruitment). Weights were derived using IPCW or raking and missing predictors of participation used to estimate weights were imputed. Weighting analyses to baseline and eligible increased beta coefficients for the middle temporal gyrus surface area, as well as fusiform gyrus cortical thickness. Alternatively, the beta coefficient for the rostral anterior cingulate decreased. Removing one group of variables used for estimating weights resulted in the weighted regression coefficient moving closer to the unweighted regression coefficient. In addition, we found considerably different beta coefficients for most surface area regions and all thickness measures when we did not impute missing covariate data. Our findings highlight the importance of using inverse probability weighting (IPW) in the neuroimaging field, especially in the context of mental health\u2010related research. We found that including all variables related to exposure\u2010outcome in the IPW model and combining IPW with multiple imputations can help reduce bias. We encourage future psychiatric neuroimaging studies to define their target population, collect information on eligible but not included participants and use inverse probability of censoring weighting (IPCW) to reduce selection bias.\n                  <\/jats:p>","DOI":"10.1002\/hbm.26562","type":"journal-article","created":{"date-parts":[[2024,4,9]],"date-time":"2024-04-09T02:10:34Z","timestamp":1712628634000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["<scp>Attention\u2010deficit hyperactivity disorder<\/scp>\n                    symptoms and brain morphology: Addressing potential selection bias with inverse probability weighting"],"prefix":"10.1002","volume":"45","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-4861-880X","authenticated-orcid":false,"given":"Annet","family":"Dijkzeul","sequence":"first","affiliation":[{"name":"Department of Child and Adolescent Psychiatry Erasmus MC University Medical Center Rotterdam\u2010Sophia Children's Hospital  Rotterdam The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Henning","family":"Tiemeier","sequence":"additional","affiliation":[{"name":"Department of Child and Adolescent Psychiatry Erasmus MC University Medical Center Rotterdam\u2010Sophia Children's Hospital  Rotterdam The Netherlands"},{"name":"Department of Social and Behavioral Sciences Harvard T.H. Chan School of Public Health  Boston Massachusetts USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ryan L.","family":"Muetzel","sequence":"additional","affiliation":[{"name":"Department of Child and Adolescent Psychiatry Erasmus MC University Medical Center Rotterdam\u2010Sophia Children's Hospital  Rotterdam The Netherlands"},{"name":"Department of Radiology and Nuclear Medicine Erasmus MC University Medical Center Rotterdam  Rotterdam The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jeremy A.","family":"Labrecque","sequence":"additional","affiliation":[{"name":"Department of Epidemiology Erasmus MC University Medical Center Rotterdam  Rotterdam The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2024,4,8]]},"reference":[{"key":"e_1_2_9_2_1","doi-asserted-by":"publisher","DOI":"10.1176\/appi.books.9780890425596"},{"key":"e_1_2_9_3_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10654-019-00550-1"},{"key":"e_1_2_9_4_1","doi-asserted-by":"publisher","DOI":"10.1093\/aje\/kwy002"},{"key":"e_1_2_9_5_1","doi-asserted-by":"crossref","unstructured":"Dall'Aglio L. Kim H. H. Lamballais S. Labrecque J. Muetzel R. L. &Tiemeier H.(2022).Attention deficit hyperactivity disorder symptoms and brain morphology: Examining confounding bias. medRxiv.https:\/\/doi.org\/10.1101\/2022.05.03.22274414","DOI":"10.7554\/eLife.78002.sa2"},{"key":"e_1_2_9_6_1","volume-title":"Brief symptom inventory. 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