文章基本信息

标题：Profile Likelihood Estimation of the Correlation Coefficient in the Presence of Left, Right or Interval Censoring and Missing Data
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作者：Yanming Li ; Brenda W. Gillespie ; Kerby Shedden 等
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.