Multilevel logistic regression for polytomous data and rankings

DOI10.1007/BF02294801zbMath1306.62503OpenAlexW2072983788WikidataQ60655842 ScholiaQ60655842MaRDI QIDQ2259872

Anders Skrondal, Sophia Rabe-Hesketh

Publication date: 5 March 2015

Published in: Psychometrika (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf02294801

zbMATH Keywords

permutationsrandom coefficient modelsrankingsfactor modelsdiscrete choicemultilevel modelsnominal datapolytomous datafirst choicegeneralized linear latent and mixed models

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) History, political science (91F10) Applications of statistics to psychology (62P15)

Related Items (14)

Maximum likelihood estimation of limited and discrete dependent variable models with nested random effects ⋮ A recursive partitioning method for the prediction of preference rankings based upon Kemeny distances ⋮ The Bradley-Terry regression trunk approach for modeling preference data with small trees ⋮ A multilevel multinomial logit model for the analysis of graduates' skills ⋮ Correcting for covariate measurement error in logistic regression using nonparametric maximum likelihood estimation ⋮ Estimating crude cumulative incidences through multinomial logit regression on discrete cause-specific hazards ⋮ Generalized multilevel structural equation modeling ⋮ Thurstonian-based analyses: past, present, and future utilities ⋮ Classical latent variable models for medical research ⋮ Latent Variable Modelling: A Survey* ⋮ Multilevel and latent variable modeling with composite links and exploded likelihoods ⋮ Discrete choice models for ordinal response variables: a generalization of the stereotype model ⋮ Efficient likelihood estimation of generalized structural equation models with a mix of normal and nonnormal responses ⋮ Modelling shelter choices in a class of mixture models for ordinal responses

Uses Software

• Stata
• GLLAMM
• MIXNO

Cites Work

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