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Finite Mixture Modeling with Mixture Outcomes Using the EM Algorithm

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  1. Marco Guerra & Francesca Bassi & José G. Dias, 2020. "A Multiple-Indicator Latent Growth Mixture Model to Track Courses with Low-Quality Teaching," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 147(2), pages 361-381, January.
  2. Lu, Xiaosun & Huang, Yangxin & Zhu, Yiliang, 2016. "Finite mixture of nonlinear mixed-effects joint models in the presence of missing and mismeasured covariate, with application to AIDS studies," Computational Statistics & Data Analysis, Elsevier, vol. 93(C), pages 119-130.
  3. Debra A. Murphy & Mary-Lynn Brecht & Diane Herbeck & Elizabeth Evans & David Huang & Yih-Ing Hser, 2008. "Longitudinal HIV Risk Behavior Among the Drug Abuse Treatment Outcome Studies (DATOS) Adult Sample," Evaluation Review, , vol. 32(1), pages 83-112, February.
  4. Zhenghao Zeng & Yuqi Gu & Gongjun Xu, 2023. "A Tensor-EM Method for Large-Scale Latent Class Analysis with Binary Responses," Psychometrika, Springer;The Psychometric Society, vol. 88(2), pages 580-612, June.
  5. Park, Nan S. & Lee, Beom S. & Sun, Fei & Vazsonyi, Alexander T. & Bolland, John M., 2010. "Pathways and predictors of antisocial behaviors in African American adolescents from poor neighborhoods," Children and Youth Services Review, Elsevier, vol. 32(3), pages 409-415, March.
  6. Reising, Kim & Ttofi, Maria M. & Farrington, David P. & Piquero, Alex R., 2019. "Depression and anxiety outcomes of offending trajectories: A systematic review of prospective longitudinal studies," Journal of Criminal Justice, Elsevier, vol. 62(C), pages 3-15.
  7. Cho, Sujung & Lee, Yung Hyeock, 2020. "Assessing self-control and strain of delinquent peer association trajectories within developmental perspectives: A latent class growth analysis approach," Children and Youth Services Review, Elsevier, vol. 109(C).
  8. Qi Chen, 2012. "The Impact of Ignoring a Level of Nesting Structure in Multilevel Mixture Model," SAGE Open, , vol. 2(1), pages 21582440124, January.
  9. Yuan Liu & Hongyun Liu, 2019. "Effects of Distance and Shape on the Estimation of the Piecewise Growth Mixture Model," Journal of Classification, Springer;The Classification Society, vol. 36(3), pages 659-677, October.
  10. Silvia Bacci & Bruno Bertaccini, 2022. "A Mixture Hidden Markov Model to Mine Students’ University Curricula," Data, MDPI, vol. 7(2), pages 1-19, February.
  11. Fokoué, Ernest, 2005. "Mixtures of factor analyzers: an extension with covariates," Journal of Multivariate Analysis, Elsevier, vol. 95(2), pages 370-384, August.
  12. Silvia Cagnone & Cinzia Viroli, 2014. "A factor mixture model for analyzing heterogeneity and cognitive structure of dementia," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 98(1), pages 1-20, January.
  13. Michael Prendergast & David Huang & Yih-Ing Hser, 2008. "Patterns of Crime and Drug Use Trajectories in Relation to Treatment Initiation and 5-Year Outcomes," Evaluation Review, , vol. 32(1), pages 59-82, February.
  14. Elena Lobo & Patricia Gracia-García & Antonio Lobo & Pedro Saz & Concepción De-la-Cámara, 2021. "Differences in Trajectories and Predictive Factors of Cognition over Time in a Sample of Cognitively Healthy Adults, in Zaragoza, Spain," IJERPH, MDPI, vol. 18(13), pages 1-13, July.
  15. Benjamin Agbo & Hussain Al-Aqrabi & Richard Hill & Tariq Alsboui, 2022. "Missing Data Imputation in the Internet of Things Sensor Networks," Future Internet, MDPI, vol. 14(5), pages 1-16, May.
  16. Cho, Sujung & Harper, Shannon B. & Kim, Youngsik, 2022. "Identifying revictimization trajectories among adolescent girls using latent class growth analysis: An examination of state dependence and population heterogeneity," Children and Youth Services Review, Elsevier, vol. 132(C).
  17. Heike Heidemeier & Anja Göritz, 2013. "Individual Differences in How Work and Nonwork Life Domains Contribute to Life Satisfaction: Using Factor Mixture Modeling for Classification," Journal of Happiness Studies, Springer, vol. 14(6), pages 1765-1788, December.
  18. Xiaosun Lu & Yangxin Huang & Rong Zhou, 2016. "Joint analysis of nonlinear heterogeneous longitudinal data and binary outcome: an application to AIDS clinical studies," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(15), pages 2713-2728, November.
  19. repec:plo:pone00:0209321 is not listed on IDEAS
  20. Heike Heidemeier & Ursula Staudinger, 2012. "Self-Evaluation Processes in Life Satisfaction: Uncovering Measurement Non-Equivalence and Age-Related Differences," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 105(1), pages 39-61, January.
  21. Liu, Yue & Liu, Lei & Zhou, Jianhui, 2015. "Joint latent class model of survival and longitudinal data: An application to CPCRA study," Computational Statistics & Data Analysis, Elsevier, vol. 91(C), pages 40-50.
  22. Maura Mezzetti & Daniele Borzelli & Andrea d’Avella, 2022. "A Bayesian approach to model individual differences and to partition individuals: case studies in growth and learning curves," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(5), pages 1245-1271, December.
  23. Brian Francis & Jiayi Liu, 2015. "Modelling escalation in crime seriousness: a latent variable approach," METRON, Springer;Sapienza Università di Roma, vol. 73(2), pages 277-297, August.
  24. Jost Reinecke & Daniel Seddig, 2011. "Growth mixture models in longitudinal research," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(4), pages 415-434, December.
  25. Silvia Bacci & Francesco Bartolucci & Giulia Bettin & Claudia Pigini, 2017. "A mixture growth model for migrants' remittances: An application to the German Socio-Economic Panel," Mo.Fi.R. Working Papers 145, Money and Finance Research group (Mo.Fi.R.) - Univ. Politecnica Marche - Dept. Economic and Social Sciences.
  26. Chung, Hwan & Chang, Hsiu-Ching, 2012. "Bayesian approaches to the model selection problem in the analysis of latent stage-sequential process," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4097-4110.
  27. Yangxin Huang & Xiaosun Lu & Jiaqing Chen & Juan Liang & Miriam Zangmeister, 2018. "Joint model-based clustering of nonlinear longitudinal trajectories and associated time-to-event data analysis, linked by latent class membership: with application to AIDS clinical studies," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 24(4), pages 699-718, October.
  28. Yao Zheng & H. Harrington Cleveland & Peter C. M. Molenaar & Kitty S. Harris, 2015. "An Alternative Framework to Investigating and Understanding Intraindividual Processes in Substance Abuse Recovery," Evaluation Review, , vol. 39(2), pages 229-254, April.
  29. Roberta Adorni & Andrea Greco & Marco D’Addario & Francesco Zanatta & Francesco Fattirolli & Cristina Franzelli & Alessandro Maloberti & Cristina Giannattasio & Patrizia Steca, 2022. "Sense of Coherence Predicts Physical Activity Maintenance and Health-Related Quality of Life: A 3-Year Longitudinal Study on Cardiovascular Patients," IJERPH, MDPI, vol. 19(8), pages 1-14, April.
  30. Jin, Huaiping & Shi, Lixian & Chen, Xiangguang & Qian, Bin & Yang, Biao & Jin, Huaikang, 2021. "Probabilistic wind power forecasting using selective ensemble of finite mixture Gaussian process regression models," Renewable Energy, Elsevier, vol. 174(C), pages 1-18.
  31. Caili Liu & Yong Wei & Yu Ling & E. Scott Huebner & Yifang Zeng & Qin Yang, 2020. "Identifying Trajectories of Chinese High School Students’ Depressive Symptoms: an Application of Latent Growth Mixture Modeling," Applied Research in Quality of Life, Springer;International Society for Quality-of-Life Studies, vol. 15(3), pages 775-789, July.
  32. David Aristei & Silvia Bacci & Francesco Bartolucci & Silvia Pandolfi, 2021. "A bivariate finite mixture growth model with selection," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 15(3), pages 759-793, September.
  33. Kim, Dong Ha, 2020. "Applying the social-ecological framework on the pattern of longitudinal trajectory of truancy in South Korean adolescents," Children and Youth Services Review, Elsevier, vol. 119(C).
  34. Seuk Yen Phoong & Shi Ling Khek & Seuk Wai Phoong, 2022. "The Bibliometric Analysis on Finite Mixture Model," SAGE Open, , vol. 12(2), pages 21582440221, May.
  35. Kiero Guerra-Peña & Zoilo Emilio García-Batista & Sarah Depaoli & Luis Eduardo Garrido, 2020. "Class enumeration false positive in skew-t family of continuous growth mixture models," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-19, April.
  36. Soo-Bi Lee & Min-Ji Yu & Myeong-Sook Yoon, 2021. "A Longitudinal Change Patterns of Depression and Its Relationship with Socioeconomic Deprivation among Middle-Aged Adults in South Korea," IJERPH, MDPI, vol. 18(24), pages 1-12, December.
  37. Landry, Craig & Remar, Daniel & Twinkle, Roy, 2022. "Economic Value of Restaurant Safety Measures and Propensity to Dine during the COVID-19 Pandemic," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322234, Agricultural and Applied Economics Association.
  38. Isabelle Archambault & Véronique Dupéré, 2017. "Joint trajectories of behavioral, affective, and cognitive engagement in elementary school," The Journal of Educational Research, Taylor & Francis Journals, vol. 110(2), pages 188-198, March.
  39. Patrick Sturgis & Louise Sullivan, 2008. "Exploring social mobility with latent trajectory groups," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(1), pages 65-88, January.
  40. Proust-Lima, Cécile & Philipps, Viviane & Liquet, Benoit, 2017. "Estimation of Extended Mixed Models Using Latent Classes and Latent Processes: The R Package lcmm," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 78(i02).
  41. Janine Stone & Christopher Goemans & Marco Costanigro, 2019. "Variation in Water Demand Responsiveness to Utility Policies and Weather: A Latent-Class Model," Water Economics and Policy (WEP), World Scientific Publishing Co. Pte. Ltd., vol. 6(01), pages 1-33, September.
  42. Karb, Rebecca A. & Elliott, Michael R. & Dowd, Jennifer B. & Morenoff, Jeffrey D., 2012. "Neighborhood-level stressors, social support, and diurnal patterns of cortisol: The Chicago Community Adult Health Study," Social Science & Medicine, Elsevier, vol. 75(6), pages 1038-1047.
  43. Chongmin Na & Thomas A. Loughran & Raymond Paternoster, 2015. "On the Importance of Treatment Effect Heterogeneity in Experimentally-Evaluated Criminal Justice Interventions," Journal of Quantitative Criminology, Springer, vol. 31(2), pages 289-310, June.
  44. Williams, John & Temme, Dirk & Hildebrandt, Lutz, 2002. "A Monte Carlo study of structural equation models for finite mixtures," SFB 373 Discussion Papers 2002,48, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  45. Getachew A. Dagne, 2016. "A growth mixture Tobit model: application to AIDS studies," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(7), pages 1174-1185, July.
  46. Jumin Park & Debra K. Moser & Kathleen Griffith & Jeffrey R. Harring & Meg Johantgen, 2019. "Exploring Symptom Clusters in People With Heart Failure," Clinical Nursing Research, , vol. 28(2), pages 165-181, February.
  47. Pietro Lovaglio & Mario Mezzanzanica, 2013. "Classification of longitudinal career paths," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(2), pages 989-1008, February.
  48. Shen-Ming Lee & Phuoc-Loc Tran & Truong-Nhat Le & Chin-Shang Li, 2023. "Prediction of a Sensitive Feature under Indirect Questioning via Warner’s Randomized Response Technique and Latent Class Model," Mathematics, MDPI, vol. 11(2), pages 1-21, January.
  49. Wei Zhao & Limin Peng & John Hanfelt, 2022. "Semiparametric latent class analysis of recurrent event data," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(4), pages 1175-1197, September.
  50. Bacci, Silvia & Bartolucci, Francesco & Pigini, Claudia & Signorelli, Marcello, 2014. "A finite mixture latent trajectory model for hirings and separations in the labor market," MPRA Paper 59730, University Library of Munich, Germany.
  51. Anthony, Elizabeth K. & Robbins, Danielle E., 2013. "A latent class analysis of resilient development among early adolescents living in public housing," Children and Youth Services Review, Elsevier, vol. 35(1), pages 82-90.
  52. Zhou, Xingcai & Liu, Xinsheng, 2008. "The EM algorithm for the extended finite mixture of the factor analyzers model," Computational Statistics & Data Analysis, Elsevier, vol. 52(8), pages 3939-3953, April.
  53. Charest, Émilie & Gagné, Marie-Hélène, 2019. "Service providers' initial stance toward the adoption of an evidence-based parenting program," Children and Youth Services Review, Elsevier, vol. 104(C), pages 1-1.
  54. Jaeun Choi & Donglin Zeng & Andrew F. Olshan & Jianwen Cai, 2018. "Joint modeling of survival time and longitudinal outcomes with flexible random effects," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 24(1), pages 126-152, January.
  55. Chiara Masci & Francesca Ieva & Tommaso Agasisti & Anna Maria Paganoni, 2021. "Evaluating class and school effects on the joint student achievements in different subjects: a bivariate semiparametric model with random coefficients," Computational Statistics, Springer, vol. 36(4), pages 2337-2377, December.
  56. Proust-Lima, Cécile & Joly, Pierre & Dartigues, Jean-François & Jacqmin-Gadda, Hélène, 2009. "Joint modelling of multivariate longitudinal outcomes and a time-to-event: A nonlinear latent class approach," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 1142-1154, February.
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  58. Casey Codd & Robert Cudeck, 2014. "Nonlinear Random-Effects Mixture Models for Repeated Measures," Psychometrika, Springer;The Psychometric Society, vol. 79(1), pages 60-83, January.
  59. Tian, Amy Wei & Meyer, John P. & Ilic-Balas, Tatjana & Espinoza, Jose A. & Pepper, Susan, 2023. "In search of the pseudo-transformational leader: A person-centered approach," Journal of Business Research, Elsevier, vol. 158(C).
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  61. Christina Bentrup, 2020. "The dual trajectory approach: detecting developmental behavioural overlaps in longitudinal and intergenerational research," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(1), pages 43-65, February.
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  63. Zachary K. Collier & Haobai Zhang & Bridgette Johnson, 2021. "Finite Mixture Modeling for Program Evaluation: Resampling and Pre-processing Approaches," Evaluation Review, , vol. 45(6), pages 309-333, December.
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