Literature DB >> 17943708

Analysis of a nonsusceptible fraction with current status data.

Richard J Cook1, Bethany J G White, Grace Y Yi, Ker-Ai Lee, Theodore E Warkentin.   

Abstract

In studies involving subclinical events, times of events are often subject to interval censoring since their occurrence is only detected at inspection times. When individuals are event-free at an initial time and a single follow-up inspection is made, current status data are obtained. In many settings, however, the population comprised a susceptible and a nonsusceptible subpopulation, where only susceptible individuals will go on to experience the event. Then interest often lies primarily in identifying prognostic variables for susceptibility, and secondarily in the event time distribution among the susceptible individuals. We give a simple mixture model that facilitates estimation of the proportion of susceptible individuals, covariate effects on the odds of susceptibility, and the event time distribution under a current status observation scheme. Asymptotic relative efficiency of maximum likelihood estimators is considered based on the Fisher information for a variety of settings. EM algorithms are proposed for parametric, weakly parametric, and nonparametric estimation of the event time distribution. The methods are applied to motivating studies examining an immunological response to low molecular weight heparin in patients undergoing orthopedic surgery.

Entities:  

Mesh:

Substances:

Year:  2008        PMID: 17943708     DOI: 10.1002/sim.3102

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  3 in total

1.  A class of semiparametric cure models with current status data.

Authors:  Guoqing Diao; Ao Yuan
Journal:  Lifetime Data Anal       Date:  2018-02-08       Impact factor: 1.588

2.  Nonparametric tests for stratified additive hazards model based on current status data.

Authors:  Xiaodong Fan; Shi-Shun Zhao; Qingchun Zhang; Jianguo Sun
Journal:  J Appl Stat       Date:  2019-12-26       Impact factor: 1.416

3.  A score test for comparing cross-sectional survival data with a fraction of non-susceptible patients and its application in clinical immunology.

Authors:  Sarah Flora Jonas; Cyprien Mbogning; Signe Hässler; Philippe Broët
Journal:  PLoS One       Date:  2017-06-30       Impact factor: 3.240

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.