Abstract
AbstractA model-dependent approach for multivariate multilevel normal modelling that accounts for informative sampling of group and unit level population elements is developed. The approach involves extracting the multilevel model holding for the sample data, given the selected sample, as a function of the corresponding population model and the sample selection probabilities, and then fitting the resulting sample model using Bayesian methods. A model-based simulation study is carried out to study the performance of our approach under one scenario motivated by a Brazilian nationwide proficiency assessment exercise. Results indicate that our approach enables improved inference under the informative sampling considered.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Journal of the Royal Statistical Society Series A: Statistics in Society
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
