Inference in nonparametric current status models with covariates

2007/10/09 by Odile Pons, Pons, Odile
Mathematics · #60J25 #62A10 #Advanced Causal Inference Techniques #FOS: Mathematics #G2G05 (Primary) #Statistical Methods and Bayesian Inference #Statistical Methods and Inference #Statistics Theory (math.ST) #math.ST #msc:60J25 #msc:62A10 #msc:G2G05 #stat.TH

paper · pdf · doi:10.48550/arxiv.0710.1690

Submitted to the Electronic Journal of Statistics (http://www.i-journals.org/ejs/) by the Institute of Mathematical Statistics (http://www.imstat.org)

arxiv created 2007/10/09 · openalex publication_date 2007/10/09 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

In interval censored models with current status observations, the variables are indicators of the presence of individuals on observation intervals and covariates. When several individuals share the same observation interval, a simple procedure provides new estimators for the distribution of the observation times and their intensity, in a closed form. They are n^1/2-consistent for piece-wise constant covariates. Estimators of the sample-sizes are deduced and asymptotic χ² tests for independence of the observations on consecutive intervals and for independence between consecutive classes for the observed individuals are proposed.

Related

• Smooth plug-in inverse estimators in the current status continuous mark model
• The bivariate current status model
• Likelihood ratio type two-sample tests for current status data
• Bayesian Nonparametric Bivariate Survival Regression for Current Status Data
• Nonparametric Estimation in Uniform Deconvolution and Interval Censoring