Assessment of School Performance Through a Multilevel Latent Markov Rasch Model
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- Sun-Joo Cho & Amanda P. Goodwin, 2017. "Modeling Learning in Doubly Multilevel Binary Longitudinal Data Using Generalized Linear Mixed Models: An Application to Measuring and Explaining Word Learning," Psychometrika, Springer;The Psychometric Society, vol. 82(3), pages 846-870, September.
- Montanari, Giorgio E. & Doretti, Marco & Bartolucci, Francesco, 2017. "A multilevel latent Markov model for the evaluation of nursing homes' performance," MPRA Paper 80691, University Library of Munich, Germany.
- Tommaso Agasisti & Francesca Ieva & Anna Maria Paganoni, 2017. "Heterogeneity, school-effects and the North/South achievement gap in Italian secondary education: evidence from a three-level mixed model," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 26(1), pages 157-180, March.
- F. Bartolucci & A. Farcomeni & F. Pennoni, 2014.
"Latent Markov models: a review of a general framework for the analysis of longitudinal data with covariates,"
TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(3), pages 433-465, September.
- Bartolucci, Francesco & Farcomeni, Alessio & Pennoni, Fulvia, 2012. "Latent Markov models: a review of a general framework for the analysis of longitudinal data with covariates," MPRA Paper 39023, University Library of Munich, Germany.
- Yang Liu & Xiaojing Wang, 2020. "Bayesian Nonparametric Monotone Regression of Dynamic Latent Traits in Item Response Theory Models," Journal of Educational and Behavioral Statistics, , vol. 45(3), pages 274-296, June.
- Qi Chen & Wen Luo & Gregory J. Palardy & Ryan Glaman & Amber McEnturff, 2017. "The Efficacy of Common Fit Indices for Enumerating Classes in Growth Mixture Models When Nested Data Structure Is Ignored," SAGE Open, , vol. 7(1), pages 21582440177, March.
- Tullio, Federico & Bartolucci, Francesco, 2019. "Evaluating time-varying treatment effects in latent Markov models: An application to the effect of remittances on poverty dynamics," MPRA Paper 91459, University Library of Munich, Germany.
- Michela Gnaldi & Silvia Bacci & Francesco Bartolucci, 2016. "A multilevel finite mixture item response model to cluster examinees and schools," 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. 10(1), pages 53-70, March.
- Bartolucci, Francesco & Lupparelli, Monia, 2012. "Nested hidden Markov chains for modeling dynamic unobserved heterogeneity in multilevel longitudinal data," MPRA Paper 40588, University Library of Munich, Germany.
- Antonello Maruotti & Jan Bulla & Tanya Mark, 2019. "Assessing the influence of marketing activities on customer behaviors: a dynamic clustering approach," METRON, Springer;Sapienza Università di Roma, vol. 77(1), pages 19-42, April.
- F. Bartolucci & A. Farcomeni & F. Pennoni, 2014. "Rejoinder on: Latent Markov models: a review of a general framework for the analysis of longitudinal data with covariates," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(3), pages 484-486, September.
- Leonardo Grilli & Carla Rampichini, 2015. "Specification of random effects in multilevel models: a review," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(3), pages 967-976, May.
- Giorgio E. Montanari & Marco Doretti, 2019. "Ranking Nursing Homes’ Performances Through a Latent Markov Model with Fixed and Random Effects," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 146(1), pages 307-326, November.
- Francesco Bartolucci & Fulvia Pennoni & Giorgio Vittadini, 2016.
"Causal Latent Markov Model for the Comparison of Multiple Treatments in Observational Longitudinal Studies,"
Journal of Educational and Behavioral Statistics, , vol. 41(2), pages 146-179, April.
- Bartolucci, Francesco & Pennoni, Fulvia & Vittadini, Giorgio, 2015. "Causal latent Markov model for the comparison of multiple treatments in observational longitudinal studies," MPRA Paper 66492, University Library of Munich, Germany.
- Francesca Bassi & Bruno Scarpa, 2015. "Latent class modeling of markers of day-specific fertility," METRON, Springer;Sapienza Università di Roma, vol. 73(2), pages 263-276, August.
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Keywordsbinary longitudinal data; cognitive achievement; Expectation-Maximization algorithm; school effectiveness;
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