Analysing ordinal longitudinal survey data: Generalised estimating equations approach

DOI10.1093/biomet/87.4.837zbMath1028.62009OpenAlexW2043572713MaRDI QIDQ2739334

Milorad S. Kovačević, Brajendra Chandra Sutradhar

Publication date: 29 January 2004

Published in: Biometrika (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1093/biomet/87.4.837

zbMATH Keywords

contingency tablelongitudinal autocorrelationmultinomial logistic distributionmultivariate ordinal categorical datastructural correlationsurvey weight

Mathematics Subject Classification ID

Sampling theory, sample surveys (62D05) General nonlinear regression (62J02)

Related Items (13)

Inferences in binary dynamic fixed models in a semi-parametric setup ⋮ Investigating impacts of complex sampling on latent growth curve modelling ⋮ On binary longitudinal mixed models in adaptive clinical trials ⋮ Semi-parametric dynamic models for longitudinal ordinal categorical data ⋮ Dynamic Models for Longitudinal Ordinal Non-stationary Categorical Data ⋮ Penalized Generalized Quasi-Likelihood Based Variable Selection for Longitudinal Data ⋮ Variable selection and estimation for longitudinal survey data ⋮ Regression theory for categorical time series ⋮ An overview on regression models for discrete longitudinal responses ⋮ Two stage cluster sampling based asymptotic inferences in survey population models for longitudinal count and categorical data ⋮ Survival analysis based on the proportional hazards model and survey data ⋮ Multinomial logistic mixed models for clustered categorical data in a complex survey sampling setup ⋮ Weighted quantile regression for longitudinal data

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