Pseudo-likelihood and quasi-likelihood estimation for complex sampling schemes

DOI10.1016/0167-9473(92)90114-UzbMath0800.62430MaRDI QIDQ1330509

V. Pereyra

Publication date: 20 September 1994

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

zbMATH Keywords

logistic regressionquasi-likelihoodpseudo-likelihoodweighted least squaressampling scheme

Mathematics Subject Classification ID

Generalized linear models (logistic models) (62J12) Probabilistic methods, stochastic differential equations (65C99)

Related Items (8)

Testing linear hypotheses in logistic regression analysis with complex sample survey data based on phi-divergence measures ⋮ Modelling Overdispersion for Complex Survey Data ⋮ Analysis of Categorical Data for Complex Surveys ⋮ Bayesian weighted inference from surveys ⋮ Pretest estimation in combining probability and non-probability samples ⋮ Minimum phi-divergence estimators for multinomial logistic regression with complex sample design ⋮ Multinomial logistic mixed models for clustered categorical data in a complex survey sampling setup ⋮ Analysis of domain means in complex surveys

Cites Work

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• Extra-Binomial Variation in Logistic Linear Models
• Weighted least-squares and quasilikelihood estimation for categorical data under singular models
• Pseudo maximum likelihood estimation: Theory and applications
• Logistic regression analysis of sample survey data
• On the Variances of Asymptotically Normal Estimators from Complex Surveys
• SOME MODELS FOR OVERDISPERSED BINOMIAL DATA
• Estimation of Reliability in Field-Performance Studies
• Strategies in the Multivariate Analysis of Data from Complex Surveys
• Efficiency of pseudolikelihood estimation for simple Gaussian fields

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