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http://hdl.handle.net/1942/21028
Title: | Clusters with random size: maximum likelihood versus weighted estimation | Authors: | HERMANS, Lisa MOLENBERGHS, Geert Kenward, M.G. VAN DER ELST, Wim Nassiri, Vahid AERTS, Marc VERBEKE, Geert |
Issue Date: | 2015 | Source: | Friedl, Herwig; Wagner, Helga (Ed.). Proceedings of the 30th International Workshop on Statistical Modelling, p. 215-220 | Abstract: | There are many contemporary designs that do not use a random sample of a fixed, a priori determined size. In case of informative cluster sizes, the cluster size is influenced by the the cluster’s data, but here we cope with some issues that even occur when the cluster size and the data are unrelated. First, fitting models to clusters of varying sizes is often more complicated than when all cluster have the same size. Secondly, in such cases, there usually is no so-called complete sufficient statistic (Molenberghs et al., 2014). | Notes: | E-mail for correspondence: lisa.hermans@uhasselt.be | Keywords: | likelihood inference; pseudo-likelihood; random cluster size | Document URI: | http://hdl.handle.net/1942/21028 | Rights: | This paper was published as a part of the proceedings of the 30th International Workshop on Statistical Modelling, Johannes Kepler Universit¨at Linz, 6–10 July 2015. The copyright remains with the author(s). Permission to reproduce or extract any parts of this abstract should be requested from the author(s). | Category: | C2 | Type: | Proceedings Paper |
Appears in Collections: | Research publications |
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IWSM-2015-Proceedings-Vol1.215-220.pdf | 458.65 kB | Adobe PDF | View/Open |
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