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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 |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Paper_Published.pdf | 1.86 MB | Adobe PDF | View/Open |
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