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  • 标题:The Shortest Width Confidence Interval for Odds Ratio in Logistic Regression
  • 本地全文:下载
  • 作者:Eugene Demidenko
  • 期刊名称:Open Journal of Statistics
  • 印刷版ISSN:2161-718X
  • 电子版ISSN:2161-7198
  • 出版年度:2012
  • 卷号:2
  • 期号:3
  • 页码:305-308
  • DOI:10.4236/ojs.2012.23037
  • 出版社:Scientific Research Publishing
  • 摘要:The shortest width confidence interval (CI) for odds ratio (OR) in logistic regression is developed based on a theorem proved by Dahiya and Guttman (1982). When the variance of the logistic regression coefficient estimate is small, the shortest width CI is close to the regular Wald CI obtained by exponentiating the CI for the regression coefficient estimate. However, when the variance increases, the optimal CI may be up to 25% narrower. It is demonstrated that the shortest width CI is favorable because it has a smaller probability of covering the wrong OR value compared with the standard CI. The closed-form iterations based on the Newton's algorithm are provided, and the R function is supplied. A simulation study confirms the superior properties of the new CI for OR in small sample. Our method is illustrated with eight studies on parity as a preventive factor against bladder cancer in women.
  • 关键词:Bladder Cancer; Coverage Probability; Logistic Regression; Newton’s Algorithm
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