On the accelerated failure time model for current status and interval censored data
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Publication:5503399
DOI10.1093/biomet/93.2.329zbMath1153.62362OpenAlexW1913380164MaRDI QIDQ5503399
Publication date: 15 January 2009
Published in: Biometrika (Search for Journal in Brave)
Full work available at URL: https://biostats.bepress.com/harvardbiostat/paper14
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Risk prediction with imperfect survival outcome information from electronic health records ⋮ Developing and evaluating risk prediction models with panel current status data ⋮ “Smooth” Semiparametric Regression Analysis for Arbitrarily Censored Time-to-Event Data ⋮ Maximum approximate likelihood estimation in accelerated failure time model for interval‐censored data ⋮ Semiparametric least-squares regression with doubly-censored data ⋮ A transformation approach for the analysis of interval-censored failure time data ⋮ Cox regression for current status data with mismeasured covariates ⋮ A Semiparametric Regression Method for Interval-Censored Data ⋮ Using the accelerated failure time model to analyze current status data with misclassified covariates ⋮ Kernel machines for current status data ⋮ Analysis of Current Status Data with Missing Covariates ⋮ Semiparametric Bayes' Proportional Odds Models for Current Status Data with Underreporting ⋮ Connecting Threshold Regression and Accelerated Failure Time Models
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