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http://hdl.handle.net/1942/281| Title: | Kernel weighted influence | Authors: | HENS, Niel AERTS, Marc MOLENBERGHS, Geert THIJS, Herbert VERBEKE, Geert |
Issue Date: | 2002 | Source: | Stasinopoulos, Mikos & Touloumi, Giota (Ed.) Statistical Modelling. Proceedings of the 17th International Workshop on Statistical Modelling. Statistical Modelling in Society. p. 337-342. | Abstract: | To asses the sensitivity for non-random dropout in a selection model framework, several methods were developed. None of them are without limitations. In this paper, a new method called kernel weighted influence is proposed. It uses several features of global and local influence approaches. Together with the use of nonparametric techniques, it provides a challenging new technique with a variety of options. | Keywords: | local influence; global influence; kernel Weights; missing data; sensitivity analysis | Document URI: | http://hdl.handle.net/1942/281 | Category: | C2 | Type: | Proceedings Paper |
| Appears in Collections: | Research publications |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| iwsm2002_proceedings-346-350.pdf | 510.85 kB | Adobe PDF | View/Open |
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