A practical guide to exact confidence intervals for a distribution of current status data using the binomial approach
DOI10.1007/978-3-031-12366-5_4MaRDI QIDQ6547602
Michael P. Fay, Sungwook Kim, Michael A. Proschan
Publication date: 30 May 2024
current status dataexact confidence intervalasymptotic coveragebinomial propertiesguaranteed coveragenonparametric maximum likelihood estimation (NPMLE)smoothed maximum likelihood estimation (SMLE)ABA (Approximate Binomial Approach) confidence intervalclopper and Pearson confidence intervalR package \textbf{csci}valid confidence interval
Applications of statistics to biology and medical sciences; meta analysis (62P10) Survival analysis and censored data (62Nxx)
Cites Work
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- The nonparametric bootstrap for the current status model
- Maximum smoothed likelihood estimation and smoothed maximum likelihood estimation in the current status model
- Extending the scope of empirical likelihood
- Likelihood ratio tests for monotone functions.
- The use of confidence of fiducial limits illustrated in the case of the binomial.
- Nonparametric Estimation under Shape Constraints
- Age-Specific Incidence and Prevalence: A Statistical Perspective
- Valid and Approximately Valid Confidence Intervals for Current Status Data
- Confidence Intervals for Current Status Data
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