碩士 / 淡江大學 / 統計學系碩士班 / 98 / Case-control studies are often used to explore the relationship between the rare disease and potential risk factors. When the confounding factors are difficult to be quantified, matching designs are used to control the confounding effects. But this results in highly stratum-specific intercepts. Breslow & Day (1980) adopt the conditional approach to eliminate the intercepts. In this paper, we introduce a new goodness-of-fit test which is proposed by Chen & Wang (2010). This test statistic is constructed by the difference between the estimates of the second moment of covariate which estimated by the conditional m.l.e. and nonparametric m.l.e., respectively. We assess the performance of the proposed method through simulation studies, and analyze two real datasets for illustration.
| Identifer | oai:union.ndltd.org:TW/098TKU05337015 |
| Date | January 2010 |
| Creators | Ci-Yu Fu, 傅琪鈺 |
| Contributors | 陳麗菁 |
| Source Sets | National Digital Library of Theses and Dissertations in Taiwan |
| Language | zh-TW |
| Detected Language | English |
| Type | 學位論文 ; thesis |
| Format | 47 |
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