A weighted composite likelihood approach to inference from clustered survey data under a two-level model

DOI10.1007/s13171-020-00234-zzbMath1472.62017OpenAlexW3118559993MaRDI QIDQ2051022

J. N. K. Rao, Laura Dumitrescu, Wei Qian

Publication date: 1 September 2021

Published in: Sankhyā. Series A (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s13171-020-00234-z

zbMATH Keywords

asymptotic distributionsgeneralised score testclustered survey datalikelihood-ratio type testweighted pairwise log-likelihood

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Sampling theory, sample surveys (62D05)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• On composite marginal likelihoods
• On the two-phase framework for joint model and design-based inference
• On chi-squared tests for multiway contingency tables with cell proportions estimated from survey data
• Asymptotics of estimating equations under natural conditions.
• A weighted composite likelihood approach for analysis of survey data under two-level models
• On the Variances of Asymptotically Normal Estimators from Complex Surveys
• Inference for longitudinal data from complex sampling surveys: An approach based on quadratic inference functions
• General Multi-Level Modeling with Sampling Weights