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  • 标题:Profile Likelihood Estimation of the Correlation Coefficient in the Presence of Left, Right or Interval Censoring and Missing Data
  • 本地全文:下载
  • 作者:Yanming Li ; Brenda W. Gillespie ; Kerby Shedden
  • 期刊名称:R News
  • 印刷版ISSN:1609-3631
  • 出版年度:2018
  • 卷号:10
  • 期号:2
  • 页码:159-179
  • 语种:English
  • 出版社:The R Foundation for Statistical Computing
  • 摘要:We discuss implementation of a profile likelihood method for estimating a Pearson correla tion coefficient from bivariate data with censoring and/or missing values. The method is implemented in an R package clikcorr which calculates maximum likelihood estimates of the correlation coefficient when the data are modeled with either a Gaussian or a Student t-distribution, in the presence of left, right, or interval censored and/or missing data. The R package includes functions for conducting inference and also provides graphical functions for visualizing the censored data scatter plot and profile log likelihood function. The performance of clikcorr in a variety of circumstances is evaluated through extensive simulation studies. We illustrate the package using two dioxin exposure datasets.
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