Comparison of methods of estimation for a goodness of fit test – an analytical and simulation study
Loading...
Date
Journal Title
Journal ISSN
Volume Title
Publisher
Taylor and Francis
Abstract
Multilevel modelling is a novel approach to analyse data which consist
of a hierarchical or a nested structure. With advancements in
multilevel modelling, there has been an advancement in the estimation
techniques and also in goodness-of-fit tests which are vital to
assess the fit of a model. However, these goodness-of-fit tests are
not as yet tested to be suitable for models estimated using different
estimation techniques. This study aims to conduct a comparison
of methods of estimations for use in a goodness-of-fit test which is
developed for binary response multilevel models. The comparison
is based upon the mathematical background, extensive simulations
and an application to a real-life dataset.
Description
Keywords
Estimation techniques; goodness-of-fit; marginal quasi likelihood (MQL); multilevel modelling; penalized quasi likelihood (PQL)
Citation
Vimukthini Pinto & Roshini Sooriyarachchi (2021): Comparison of methods of estimation for a goodness of fit test – an analytical and simulation study, Journal of Statistical Computation and Simulation
