Comparison of methods of estimation for a goodness of fit test – an analytical and simulation study
| 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.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.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/handle/70130/5516 | |
| 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 |