General Multi-Level Modeling with Sampling Weights

DOI10.1080/03610920500476598zbMath1084.62053OpenAlexW1998449083MaRDI QIDQ5201503

Tihomir Asparouhov

Publication date: 19 April 2006

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610920500476598

zbMATH Keywords

tablesintraclass correlationmulti-level modelssampling weightscluster sampling designsinformative selectionmulti-level mixture modelsmulti-level pseudo maximum likelihoodweights scaling

Mathematics Subject Classification ID

Multivariate analysis (62H99) Estimation in multivariate analysis (62H12) Sampling theory, sample surveys (62D05)

Related Items (11)

Importance of sampling weights in multilevel modeling of international large-scale assessment data ⋮ Evaluation of Conditional Weight Approximations for Two-Level Models ⋮ Two-stage informative cluster sampling estimation and prediction with applications for small-area models ⋮ A resampling approach to estimate variance components of multilevel models ⋮ Multi-level models can benefit from minimizing higher-order variations: an illustration using child malnutrition data ⋮ On generating plausible values for multilevel modelling with large‐scale‐assessment data ⋮ An approximate best prediction approach to small area estimation for sheet and rill erosion under informative sampling ⋮ Estimation of small area counts with the benchmarking property ⋮ A weighted composite likelihood approach to inference from clustered survey data under a two-level model ⋮ Modelling multilevel data under complex sampling designs: an empirical likelihood approach ⋮ A Sample Survey on Inactive Students: Weighting Issues in Modelling the Inactivity Status

Uses Software

• Mplus

Cites Work

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• The Role of Sampling Weights When Modeling Survey Data
• On the Variances of Asymptotically Normal Estimators from Complex Surveys
• "Equivalent Sample Size" and "Equivalent Degrees of Freedom" Refinements for Inference Using Survey Weights Under Superpopulation Models
• Weighting for Unequal Selection Probabilities in Multilevel Models
• Estimating Variance Components by Using Survey Data
• A Pseudo Maximum Likelihood Approach to Multilevel Modelling of Survey Data

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