Lifetime Data Anal - Proportional hazards regression with interval censored data using an inverse probability weight.

Tópicos

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Resumo

The prevalence of interval censored data is increasing in medical studies due to the growing use of biomarkers to define a disease progression endpoint. Interval censoring results from periodic monitoring of the progression status. For example, disease progression is established in the interval between the clinic visit where progression is recorded and the prior clinic visit where there was no evidence of disease progression. A methodology is proposed for estimation and inference on the regression coefficients in the Cox proportional hazards model with interval censored data. The methodology is based on estimating equations and uses an inverse probability weight to select event time pairs where the ordering is unambiguous. Simulations are performed to examine the finite sample properties of the estimate and a colon cancer data set is used to demonstrate its performance relative to the conventional partial likelihood estimate that ignores the interval censoring.

Resumo Limpo

preval interv censor data increas medic studi due grow use biomark defin diseas progress endpoint interv censor result period monitor progress status exampl diseas progress establish interv clinic visit progress record prior clinic visit evid diseas progress methodolog propos estim infer regress coeffici cox proport hazard model interv censor data methodolog base estim equat use invers probabl weight select event time pair order unambigu simul perform examin finit sampl properti estim colon cancer data set use demonstr perform relat convent partial likelihood estim ignor interv censor

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