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The missing\u2010at\u2010random (MAR) assumption is formulated to deal with the first two types of missingness, while to account for the informative dropout, we rely on an extra absorbing state. Estimation of the model parameters is based on the maximum likelihood method that is implemented by an expectation\u2010maximization (EM) algorithm relying on suitable recursions. The proposal is illustrated by a Monte Carlo simulation study and an application based on historical data on primary biliary cholangitis.<\/jats:p>","DOI":"10.1002\/bimj.202200016","type":"journal-article","created":{"date-parts":[[2023,4,10]],"date-time":"2023-04-10T09:41:23Z","timestamp":1681119683000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["A hidden Markov model for continuous longitudinal data with missing responses and dropout"],"prefix":"10.1002","volume":"65","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6019-8694","authenticated-orcid":false,"given":"Silvia","family":"Pandolfi","sequence":"first","affiliation":[{"name":"Department of Economics University of Perugia Perugia Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francesco","family":"Bartolucci","sequence":"additional","affiliation":[{"name":"Department of Economics University of Perugia Perugia Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fulvia","family":"Pennoni","sequence":"additional","affiliation":[{"name":"Department of Statistics and Quantitative Methods University of Milano\u2010Bicocca Milan Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2023,4,10]]},"reference":[{"key":"e_1_2_11_2_1","first-page":"267","volume-title":"Second international symposium on information theory","author":"Akaike H.","year":"1973"},{"key":"e_1_2_11_3_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.0006-341X.2002.00631.x"},{"key":"e_1_2_11_4_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.0006-341X.2000.00602.x"},{"key":"e_1_2_11_5_1","series-title":"Wiley Series in Probability and Statistics","volume-title":"An introduction to multivariate statistical analysis","author":"Anderson T.","year":"2003"},{"key":"e_1_2_11_6_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11634-013-0154-2"},{"key":"e_1_2_11_7_1","doi-asserted-by":"publisher","DOI":"10.2307\/2532201"},{"key":"e_1_2_11_8_1","doi-asserted-by":"publisher","DOI":"10.1198\/jasa.2009.0107"},{"key":"e_1_2_11_9_1","doi-asserted-by":"publisher","DOI":"10.1111\/biom.12224"},{"key":"e_1_2_11_10_1","doi-asserted-by":"publisher","DOI":"10.1002\/sim.7994"},{"key":"e_1_2_11_11_1","volume-title":"Latent Markov models for longitudinal data","author":"Bartolucci F.","year":"2013"},{"key":"e_1_2_11_12_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11749-014-0381-7"},{"key":"e_1_2_11_13_1","doi-asserted-by":"publisher","DOI":"10.18637\/jss.v081.i04"},{"key":"e_1_2_11_14_1","doi-asserted-by":"publisher","DOI":"10.1146\/annurev-statistics-040220-091910"},{"key":"e_1_2_11_15_1","doi-asserted-by":"publisher","DOI":"10.1214\/aoms\/1177697196"},{"key":"e_1_2_11_16_1","doi-asserted-by":"publisher","DOI":"10.1081\/STA-200056845"},{"key":"e_1_2_11_17_1","doi-asserted-by":"publisher","DOI":"10.1017\/9781108644181"},{"key":"e_1_2_11_18_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00180-007-0097-1"},{"key":"e_1_2_11_19_1","doi-asserted-by":"publisher","DOI":"10.1093\/jjfinec\/nbp014"},{"key":"e_1_2_11_20_1","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1111\/j.2517-6161.1972.tb00899.x","article-title":"Regression models and life\u2010tables","volume":"34","author":"Cox D. 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