{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T01:47:11Z","timestamp":1791942431499,"version":"4.3.4"},"reference-count":51,"publisher":"Wiley","issue":"23-24","license":[{"start":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T00:00:00Z","timestamp":1791849600000},"content-version":"vor","delay-in-days":12,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/100000025","name":"National Institute of Mental Health","doi-asserted-by":"publisher","award":["R01\u2010MH122473"],"award-info":[{"award-number":["R01\u2010MH122473"]}],"id":[{"id":"10.13039\/100000025","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000025","name":"National Institute of Mental Health","doi-asserted-by":"publisher","award":["R01\u2010MH107394"],"award-info":[{"award-number":["R01\u2010MH107394"]}],"id":[{"id":"10.13039\/100000025","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000266","name":"Engineering and Physical Sciences Research Council","doi-asserted-by":"publisher","award":["EP\/T021020\/1"],"award-info":[{"award-number":["EP\/T021020\/1"]}],"id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000266","name":"Engineering and Physical Sciences Research Council","doi-asserted-by":"publisher","award":["EP\/T014105\/1"],"award-info":[{"award-number":["EP\/T014105\/1"]}],"id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Statistics in Medicine"],"published-print":{"date-parts":[[2026,10]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Changepoint analysis for time series data identifies the time points for which properties about the data shift. In this paper, we are motivated by two distinct types of biomedical time series data: digital health monitoring and neuroimaging. The neuroimaging study consists of multivariate time series obtained from resting\u2010state functional magnetic resonance imaging (fMRI). The digital health monitoring data consists of binary univariate time series observed within an individual throughout the day across multiple days of activity. The goal of the analysis is to model how physical activity changes within a day over a period of 56\u2009days. The goal in the analysis of that data is to determine the association between dynamic functional connectivity (dFC), which is the interaction between different brain regions and how this interaction changes over time, and severity of non\u2010suicidal self\u2010injury (NSSI). In this paper, we leverage the framework of generalized linear mixed models to incorporate structure that is present in biomedical time series data for changepoint analysis. This structure could be, for example, the repeated measures of the time series data within an individual across multiple days or the interconnected community structure of brain networks. We embed the mixed model in a dynamic programming algorithm for detecting multiple changepoints. We evaluate the performance of our proposed method across several scenarios using simulations. Finally, we show the utility of our proposed method on our two distinct motivating applications.<\/jats:p>","DOI":"10.1002\/sim.70769","type":"journal-article","created":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T01:16:35Z","timestamp":1791940595000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Generalized Linear Mixed Models for Changepoint Analysis of Biomedical Time Series Data"],"prefix":"10.1002","volume":"45","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6472-9410","authenticated-orcid":false,"given":"Mark","family":"Fiecas","sequence":"first","affiliation":[{"name":"Division of Biostatistics and Health Data Science University of Minnesota  Minneapolis Minnesota USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0583-3960","authenticated-orcid":false,"given":"Rebecca","family":"Killick","sequence":"additional","affiliation":[{"name":"School of Mathematical Sciences Lancaster University  Lancaster UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kathryn","family":"Cullen","sequence":"additional","affiliation":[{"name":"Department of Psychiatry and Behavioral Sciences University of Minnesota  Minneapolis Minnesota USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,10,13]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"crossref","DOI":"10.1016\/j.sigpro.2019.107299","article-title":"Selective Review of Offline Change Point Detection Methods","volume":"167","author":"Truong C.","year":"2020","journal-title":"Signal Processing"},{"issue":"500","key":"e_1_2_10_3_1","doi-asserted-by":"crossref","first-page":"1590","DOI":"10.1080\/01621459.2012.737745","article-title":"Optimal Detection of Changepoints With a Linear Computational Cost","volume":"107","author":"Killick R.","year":"2012","journal-title":"Journal of the American Statistical Association"},{"key":"e_1_2_10_4_1","doi-asserted-by":"crossref","DOI":"10.1016\/j.csda.2022.107433","article-title":"A Comparison of Single and Multiple Changepoint Techniques for Time Series Data","volume":"170","author":"Shi X.","year":"2022","journal-title":"Computational Statistics & Data Analysis"},{"key":"e_1_2_10_5_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v007.i02","article-title":"Strucchange: An R Package for Testing for Structural Change in Linear Regression Models","volume":"7","author":"Zeileis A.","year":"2002","journal-title":"Journal of Statistical Software"},{"issue":"5","key":"e_1_2_10_6_1","doi-asserted-by":"crossref","first-page":"757","DOI":"10.1111\/j.1467-9892.2011.00778.x","article-title":"Changepoints in Times Series of Counts","volume":"33","author":"Franke J.","year":"2012","journal-title":"Journal of Time Series Analysis"},{"issue":"3","key":"e_1_2_10_7_1","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1080\/08982110108918663","article-title":"Identifying the Time of a Step\u2010Change in the Process Fraction Nonconforming","volume":"13","author":"Pignatiello J. J.","year":"2001","journal-title":"Quality Engineering"},{"issue":"23","key":"e_1_2_10_8_1","doi-asserted-by":"crossref","first-page":"8041","DOI":"10.1175\/JCLI-D-22-0954.1","article-title":"Good Practices and Common Pitfalls in Climate Time Series Changepoint Techniques: A Review","volume":"36","author":"Lund R. B.","year":"2023","journal-title":"Journal of Climate"},{"issue":"3","key":"e_1_2_10_9_1","doi-asserted-by":"crossref","first-page":"579","DOI":"10.1111\/rssc.12472","article-title":"Assessing Daily Patterns Using Home Activity Sensors and Within Period Changepoint Detection","volume":"70","author":"Taylor S. A.","year":"2021","journal-title":"Journal of the Royal Statistical Society. Series C, Applied Statistics"},{"issue":"4","key":"e_1_2_10_10_1","doi-asserted-by":"crossref","first-page":"907","DOI":"10.1016\/j.neuroimage.2012.03.070","article-title":"Dynamic Connectivity Regression: Determining State\u2010Related Changes in Brain Connectivity","volume":"61","author":"Cribben I.","year":"2012","journal-title":"NeuroImage"},{"key":"e_1_2_10_11_1","doi-asserted-by":"crossref","first-page":"143","DOI":"10.3389\/fncom.2013.00143","article-title":"Detecting Functional Connectivity Change Points for Single\u2010Subject fMRI Data","volume":"7","author":"Cribben I.","year":"2013","journal-title":"Frontiers in Computational Neuroscience"},{"issue":"2","key":"e_1_2_10_12_1","doi-asserted-by":"crossref","first-page":"475","DOI":"10.1111\/rssb.12079","article-title":"Multiple\u2010Change\u2010Point Detection for High Dimensional Time Series via Sparsified Binary Segmentation","volume":"77","author":"Cho H.","year":"2015","journal-title":"Journal of the Royal Statistical Society, Series B: Statistical Methodology"},{"key":"e_1_2_10_13_1","doi-asserted-by":"publisher","DOI":"10.1080\/00031305.2024.2329681"},{"issue":"27","key":"e_1_2_10_14_1","doi-asserted-by":"crossref","first-page":"5786","DOI":"10.1002\/sim.3380","article-title":"A Random Change Point Model for Assessing Variability in Repeated Measures of Cognitive Function","volume":"27","author":"Dominicus A.","year":"2008","journal-title":"Statistics in Medicine"},{"issue":"6","key":"e_1_2_10_15_1","doi-asserted-by":"crossref","first-page":"1015","DOI":"10.1002\/sim.5996","article-title":"Identifying Multiple Change Points in a Linear Mixed Effects Model","volume":"33","author":"Lai Y.","year":"2014","journal-title":"Statistics in Medicine"},{"issue":"6","key":"e_1_2_10_16_1","doi-asserted-by":"crossref","first-page":"1332","DOI":"10.1093\/ije\/30.6.1332","article-title":"Tutorial in Biostatistics: Evaluating the Impact of \u2018Critical Periods\u2019 in Longitudinal Studies of Growth Using Piecewise Mixed Effects Models","volume":"30","author":"Naumova E. N.","year":"2001","journal-title":"International Journal of Epidemiology"},{"key":"e_1_2_10_17_1","doi-asserted-by":"crossref","DOI":"10.1007\/978-0-387-47946-0","volume-title":"Linear and Generalized Linear Mixed Models and Their Applications","author":"Jiang J.","year":"2007"},{"key":"e_1_2_10_18_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v067.i01","article-title":"Fitting Linear Mixed\u2010Effects Models Using lme4","volume":"67","author":"Bates D.","year":"2015","journal-title":"Journal of Statistical Software"},{"key":"e_1_2_10_19_1","doi-asserted-by":"publisher","DOI":"10.1214\/22\u2010EJS2048"},{"issue":"4","key":"e_1_2_10_20_1","doi-asserted-by":"crossref","first-page":"480","DOI":"10.1080\/00401706.2023.2183261","article-title":"Detecting Changes in Covariance via Random Matrix Theory","volume":"65","author":"Ryan S.","year":"2023","journal-title":"Technometrics"},{"issue":"525","key":"e_1_2_10_21_1","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1080\/01621459.2017.1385466","article-title":"Changepoint Detection in the Presence of Outliers","volume":"114","author":"Fearnhead P.","year":"2019","journal-title":"Journal of the American Statistical Association"},{"issue":"1","key":"e_1_2_10_22_1","doi-asserted-by":"crossref","first-page":"388","DOI":"10.3150\/24-BEJ1732","article-title":"Cross\u2010Validation for Change\u2010Point Regression: Pitfalls and Solutions","volume":"31","author":"Pein F.","year":"2025","journal-title":"Bernoulli"},{"key":"e_1_2_10_23_1","first-page":"172","volume-title":"International Conference on Machine Learning","author":"Hocking T.","year":"2013"},{"issue":"8","key":"e_1_2_10_24_1","doi-asserted-by":"crossref","first-page":"1501","DOI":"10.1016\/j.sigpro.2005.01.012","article-title":"Using Penalized Contrasts for the Change\u2010Point Problem","volume":"85","author":"Lavielle M.","year":"2005","journal-title":"Signal Processing"},{"issue":"14","key":"e_1_2_10_25_1","doi-asserted-by":"crossref","first-page":"1997","DOI":"10.1093\/bioinformatics\/btab047","article-title":"ICN: Extracting Interconnected Communities in Gene Co\u2010Expression Networks","volume":"37","author":"Wu Q.","year":"2021","journal-title":"Bioinformatics"},{"issue":"4","key":"e_1_2_10_26_1","doi-asserted-by":"crossref","first-page":"1021","DOI":"10.1007\/s42952-022-00173-5","article-title":"Autocovariance Estimation in the Presence of Changepoints","volume":"51","author":"Gallagher C.","year":"2022","journal-title":"Journal of the Korean Statistical Society"},{"issue":"3","key":"e_1_2_10_27_1","doi-asserted-by":"crossref","first-page":"846","DOI":"10.1080\/07350015.2022.2076686","article-title":"Detection of Multiple Structural Breaks in Large Covariance Matrices","volume":"41","author":"Li Y. N.","year":"2023","journal-title":"Journal of Business & Economic Statistics"},{"key":"e_1_2_10_28_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.9529"},{"issue":"1","key":"e_1_2_10_29_1","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1162\/netn_a_00116","article-title":"Questions and Controversies in the Study of Time\u2010Varying Functional Connectivity in Resting fMRI","volume":"4","author":"Lurie D. J.","year":"2020","journal-title":"Network Neuroscience"},{"issue":"3","key":"e_1_2_10_30_1","doi-asserted-by":"crossref","first-page":"663","DOI":"10.1093\/cercor\/bhs352","article-title":"Tracking Whole\u2010Brain Connectivity Dynamics in the Resting State","volume":"24","author":"Allen E. A.","year":"2014","journal-title":"Cerebral Cortex"},{"issue":"48","key":"e_1_2_10_31_1","doi-asserted-by":"crossref","first-page":"12827","DOI":"10.1073\/pnas.1705120114","article-title":"Brain Network Dynamics Are Hierarchically Organized in Time","volume":"114","author":"Vidaurre D.","year":"2017","journal-title":"Proceedings of the National Academy of Sciences"},{"key":"e_1_2_10_32_1","doi-asserted-by":"publisher","DOI":"10.4310\/22\u2010SII730"},{"key":"e_1_2_10_33_1","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1016\/j.neuroimage.2019.02.013","article-title":"Improved State Change Estimation in Dynamic Functional Connectivity Using Hidden Semi\u2010Markov Models","volume":"191","author":"Shappell H.","year":"2019","journal-title":"NeuroImage"},{"key":"e_1_2_10_34_1","doi-asserted-by":"publisher","DOI":"10.20900\/jpbs.20230007"},{"issue":"5","key":"e_1_2_10_35_1","doi-asserted-by":"crossref","first-page":"1774","DOI":"10.1017\/S0954579421000754","article-title":"Multimodal Assessment of Sustained Threat in Adolescents With Nonsuicidal Self\u2010Injury","volume":"33","author":"Ba\u015fg\u00f6ze Z.","year":"2021","journal-title":"Development and Psychopathology"},{"issue":"4","key":"e_1_2_10_36_1","first-page":"855","article-title":"A Multi\u2010Level Examination of Cognitive Control in Adolescents With Non\u2010Suicidal Self\u2010Injury","volume":"3","author":"Ba\u015fg\u00f6ze Z.","year":"2023","journal-title":"Biological Psychiatry: Global Open Science"},{"issue":"5","key":"e_1_2_10_37_1","doi-asserted-by":"crossref","first-page":"2164","DOI":"10.1017\/S0033291721004074","article-title":"Brain Signatures in Children Who Contemplate Suicide: Learning From the Large\u2010Scale ABCD Study","volume":"53","author":"Wiglesworth A.","year":"2023","journal-title":"Psychological Medicine"},{"issue":"7615","key":"e_1_2_10_38_1","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1038\/nature18933","article-title":"A Multi\u2010Modal Parcellation of Human Cerebral Cortex","volume":"536","author":"Glasser M. F.","year":"2016","journal-title":"Nature"},{"issue":"4","key":"e_1_2_10_39_1","doi-asserted-by":"crossref","DOI":"10.1088\/1741-2560\/8\/4\/046025","article-title":"True Associations Between Resting fMRI Time Series Based on Innovations","volume":"8","author":"Christova P.","year":"2011","journal-title":"Journal of Neural Engineering"},{"key":"e_1_2_10_40_1","doi-asserted-by":"crossref","first-page":"294","DOI":"10.1016\/j.neuroimage.2014.07.045","article-title":"Impact of Autocorrelation on Functional Connectivity","volume":"102","author":"Arbabshirani M. R.","year":"2014","journal-title":"NeuroImage"},{"key":"e_1_2_10_41_1","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/j.neuroimage.2019.04.042","article-title":"Investigating the Impact of Autocorrelation on Time\u2010Varying Connectivity","volume":"197","author":"Honari H.","year":"2019","journal-title":"NeuroImage"},{"issue":"10","key":"e_1_2_10_42_1","first-page":"4719","article-title":"On the Stability of BOLD fMRI Correlations","volume":"27","author":"Laumann T. O.","year":"2017","journal-title":"Cerebral Cortex"},{"issue":"7","key":"e_1_2_10_43_1","doi-asserted-by":"crossref","first-page":"1822","DOI":"10.1038\/npp.2015.352","article-title":"Dynamic Resting\u2010State Functional Connectivity in Major Depression","volume":"41","author":"Kaiser R. H.","year":"2016","journal-title":"Neuropsychopharmacology"},{"issue":"9","key":"e_1_2_10_44_1","doi-asserted-by":"crossref","DOI":"10.3390\/brainsci12091263","article-title":"Temporal Stability of Dynamic Default Mode Network Connectivity Negatively Correlates With Suicidality in Major Depressive Disorder","volume":"12","author":"Ouyang X.","year":"2022","journal-title":"Brain Sciences"},{"key":"e_1_2_10_45_1","doi-asserted-by":"crossref","DOI":"10.3389\/fnins.2022.937145","article-title":"Aberrant Dynamic Functional Connectivity of Posterior Cingulate Cortex Subregions in Major Depressive Disorder With Suicidal Ideation","volume":"16","author":"Li W.","year":"2022","journal-title":"Frontiers in Neuroscience"},{"issue":"4","key":"e_1_2_10_46_1","doi-asserted-by":"crossref","DOI":"10.1038\/tp.2017.40","article-title":"Instability of Default Mode Network Connectivity in Major Depression: A Two\u2010Sample Confirmation Study","volume":"7","author":"Wise T.","year":"2017","journal-title":"Translational Psychiatry"},{"issue":"8","key":"e_1_2_10_47_1","doi-asserted-by":"crossref","first-page":"2918","DOI":"10.1002\/hbm.23215","article-title":"Dynamic Functional Connectivity Reveals Altered Variability in Functional Connectivity Among Patients With Major Depressive Disorder","volume":"37","author":"Demirta\u015f M.","year":"2016","journal-title":"Human Brain Mapping"},{"key":"e_1_2_10_48_1","doi-asserted-by":"crossref","first-page":"339","DOI":"10.3389\/fpsyt.2018.00339","article-title":"Aberrant Dynamic Functional Network Connectivity and Graph Properties in Major Depressive Disorder","volume":"9","author":"Zhi D.","year":"2018","journal-title":"Frontiers in Psychiatry"},{"issue":"5","key":"e_1_2_10_49_1","article-title":"Depression, Non\u2010Suicidal Self\u2010Injury, and Suicidality in Adolescents: Common and Distinct Precursors, Correlates, and Outcomes","volume":"6","author":"Ba\u015fg\u00f6ze Z.","year":"2021","journal-title":"Journal of Psychiatry and Brain Science"},{"key":"e_1_2_10_50_1","doi-asserted-by":"crossref","DOI":"10.1016\/j.jad.2025.120363","article-title":"Potential Predictors of Future Suicide Attempts in Adolescents Assigned Female at Birth","volume":"393","author":"Ba\u015fg\u00f6ze Z.","year":"2025","journal-title":"Journal of Affective Disorders"},{"key":"e_1_2_10_51_1","doi-asserted-by":"crossref","first-page":"216","DOI":"10.1016\/j.psyneuen.2018.11.004","article-title":"Hypothalamic\u2010Pituitary\u2010Adrenal Axis Dysregulation in Depressed Adolescents With Non\u2010Suicidal Self\u2010Injury","volume":"102","author":"Klimes\u2010Dougan B.","year":"2019","journal-title":"Psychoneuroendocrinology"},{"issue":"4","key":"e_1_2_10_52_1","doi-asserted-by":"crossref","first-page":"282","DOI":"10.1016\/j.cpr.2014.03.005","article-title":"Correlates of Suicide Attempts Among Self\u2010Injurers: A Meta\u2010Analysis","volume":"34","author":"Victor S. E.","year":"2014","journal-title":"Clinical Psychology Review"}],"container-title":["Statistics in Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/sim.70769","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1002\/sim.70769","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/sim.70769","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T01:16:41Z","timestamp":1791940601000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/sim.70769"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10]]},"references-count":51,"journal-issue":{"issue":"23-24","published-print":{"date-parts":[[2026,10]]}},"alternative-id":["10.1002\/sim.70769"],"URL":"https:\/\/doi.org\/10.1002\/sim.70769","archive":["Portico"],"relation":{},"ISSN":["0277-6715","1097-0258"],"issn-type":[{"value":"0277-6715","type":"print"},{"value":"1097-0258","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,10]]},"assertion":[{"value":"2025-11-03","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-09-29","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-10-13","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e70769"}}