Regression models for interval censored data using parametric pseudo-observations [PDF]
BMC Medical Research Methodology, 2021 Background Time-to-event data that is subject to interval censoring is common in the practice of medical research and versatile statistical methods for estimating associations in such settings have been limited.
Martin Nygård Johansen +3 more
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A support vector machine-based cure rate model for interval censored data. [PDF]
Stat Methods Med Res, 2023 The mixture cure rate model is the most commonly used cure rate model in the literature. In the context of mixture cure rate model, the standard approach to model the effect of covariates on the cured or uncured probability is to use a logistic function.
Pal S, Peng Y, Aselisewine W, Barui S.
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Neural network on interval-censored data with application to the prediction of Alzheimer's disease. [PDF]
Biometrics, 2023 Alzheimer's disease (AD) is a progressive and polygenic disorder that affects millions of individuals each year. Given that there have been few effective treatments yet for AD, it is highly desirable to develop an accurate model to predict the full ...
Sun T, Ding Y.
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Instrumental variable estimation of complier causal treatment effect with interval-censored data. [PDF]
Biometrics, 2023 Assessing causal treatment effect on a time‐to‐event outcome is of key interest in many scientific investigations. Instrumental variable (IV) is a useful tool to mitigate the impact of endogenous treatment selection to attain unbiased estimation of ...
Li S, Peng L.
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Parameter estimation of the incubation period of COVID-19 based on the doubly interval-censored data model. [PDF]
Nonlinear Dyn, 2021 With the spread of the novel coronavirus disease 2019 (COVID-19) around the world, the estimation of the incubation period of COVID-19 has become a hot issue.
Yin MZ, Zhu QW, Lü X.
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Assessing the accuracy of predictive models with interval-censored data. [PDF]
Biostatistics, 2022 Summary We develop methods for assessing the predictive accuracy of a given event time model when the validation sample is comprised of case \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb}
Wu Y, Cook RJ.
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A Bayesian Model for Spatial Partly Interval-Censored Data. [PDF]
Commun Stat Simul Comput, 2022 Partly interval-censored data often occur in cancer clinical trials and have been analyzed as right-censored data. Patients’ geographic information sometimes is also available and can be useful in testing treatment effects and predicting survivorship. We
Pan C, Cai B.
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A Bayesian approach for analyzing partly interval-censored data under the proportional hazards model. [PDF]
Stat Methods Med Res, 2020 Partly interval-censored time-to-event data often occur in biomedical studies of diseases where periodic medical examinations for symptoms of interest are necessary.
Pan C, Cai B, Wang L.
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Simultaneous Estimation and Variable Selection for Interval-Censored Data with Broken Adaptive Ridge Regression. [PDF]
J Am Stat Assoc, 2020 The simultaneous estimation and variable selection for Cox model has been discussed by several authors when one observes right-censored failure time data.
Zhao H, Wu Q, Li G, Sun J.
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icenReg: Regression Models for Interval Censored Data in R
Journal of Statistical Software, 2017 The non-parametric maximum likelihood estimator and semi-parametric regression models are fundamental estimators for interval censored data, along with standard fullyparametric regression models.
Clifford Anderson-Bergman
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