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  • 标题:A Note on Improving Inference of Relative Risk
  • 本地全文:下载
  • 作者:Octavia C. Y. Wong
  • 期刊名称:Open Journal of Statistics
  • 印刷版ISSN:2161-718X
  • 电子版ISSN:2161-7198
  • 出版年度:2019
  • 卷号:9
  • 期号:1
  • 页码:100-108
  • DOI:10.4236/ojs.2019.91009
  • 出版社:Scientific Research Publishing
  • 摘要:Relative risk is a popular measure to compare risk of an outcome in the exposed group to the unexposed group. By applying the delta method and Central Limit Theorem, [1] derives two approximate confidence intervals for the relative risk, and [2] approximates the confidence interval for the relative risk via the likelihood ratio statistic. Both of these approximations require sample size to be large. In this paper, by adjusting the likelihood ratio statistic obtained by [2], a new method is proposed to obtain the confidence interval for the relative risk. Simulation results showed that the proposed method is extremely accurate even when the sample size is small.
  • 关键词:Bartlett Correction;Confidence Intervals;Coverage Property;Relative Risk
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