Please use this identifier to cite or link to this item: http://archive.cmb.ac.lk:8080/xmlui/handle/70130/5516
Title: Comparison of methods of estimation for a goodness of fit test – an analytical and simulation study
Authors: Pinto, Vimukthini
Sooriyarachchi, M.R.
Keywords: Estimation techniques; goodness-of-fit; marginal quasi likelihood (MQL); multilevel modelling; penalized quasi likelihood (PQL)
Issue Date: 2021
Publisher: Taylor and Francis
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
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.
URI: http://archive.cmb.ac.lk:8080/xmlui/handle/70130/5516
Appears in Collections:Department of Statistics
Department of Statistics

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