Comparison of methods of estimation for a goodness of fit test – an analytical and simulation study

Pinto, Vimukthini; Sooriyarachchi, M.R.

dc.contributor.author	Pinto, Vimukthini
dc.contributor.author	Sooriyarachchi, M.R.
dc.date.accessioned	2021-07-13T05:29:04Z
dc.date.available	2021-07-13T05:29:04Z
dc.date.issued	2021
dc.identifier.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	en_US
dc.identifier.uri	http://archive.cmb.ac.lk:8080/xmlui/handle/70130/5516
dc.description.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.	en_US
dc.description.sponsorship	No Sponsors	en_US
dc.language.iso	en	en_US
dc.publisher	Taylor and Francis	en_US
dc.subject	Estimation techniques; goodness-of-fit; marginal quasi likelihood (MQL); multilevel modelling; penalized quasi likelihood (PQL)	en_US
dc.title	Comparison of methods of estimation for a goodness of fit test – an analytical and simulation study	en_US
dc.type	Article	en_US