Please use this identifier to cite or link to this item: http://archive.cmb.ac.lk:8080/xmlui/handle/70130/5516
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dc.contributor.authorPinto, Vimukthini-
dc.contributor.authorSooriyarachchi, M.R.-
dc.date.accessioned2021-07-13T05:29:04Z-
dc.date.available2021-07-13T05:29:04Z-
dc.date.issued2021-
dc.identifier.citationVimukthini 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 Simulationen_US
dc.identifier.urihttp://archive.cmb.ac.lk:8080/xmlui/handle/70130/5516-
dc.description.abstractMultilevel 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.sponsorshipNo Sponsorsen_US
dc.language.isoenen_US
dc.publisherTaylor and Francisen_US
dc.subjectEstimation techniques; goodness-of-fit; marginal quasi likelihood (MQL); multilevel modelling; penalized quasi likelihood (PQL)en_US
dc.titleComparison of methods of estimation for a goodness of fit test – an analytical and simulation studyen_US
dc.typeArticleen_US
Appears in Collections:Department of Statistics
Department of Statistics

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