Analyzing Recurrent Event Data With Informative Censoring
نویسندگان
چکیده
منابع مشابه
Evaluation of treatment effect based on recurrent event data with potentially informative censoring mechanism*
Rarely do we see a clinical trial with 100% completion rate. That is, all patients who were randomized to receive either the new treatment (denoted by T) or the comparator (an active control agent denoted by C or placebo denoted by P) had stayed through the entire trial period, for instance, one year study duration. Using the measurement of either the percentage of patients who dropped out the ...
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Multivariate recurrent event data are usually encountered in many clinical and longitudinal studies in which each study subject may experience multiple recurrent events. For the analysis of such data, most existing approaches have been proposed under the assumption that the censoring times are noninformative, which may not be true especially when the observation of recurrent events is terminate...
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This article deals with studies that monitor occurrences of a recurrent event for n subjects or experimental units. It is assumed that the i(th) unit is monitored over a random period [0,tau(i)]. The successive inter-event times T(i1), T(i2), ..., are assumed independent of tau(i). The random number of event occurrences over the monitoring period is K(i) = max{k in {0, 1, 2, ...} : T(i1) + T(i2...
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Consider a study where the times of occurrences of a recurrent event for n units are monitored. For the ith unit, T(i1), T(i2), …, denote the successive event interoccurrence times and this unit is monitored over a random period [0, τ(i)] with τ(i) independent of the T(ij)s. Over this monitoring period, [Formula: see text] is the random number of event occurrences. The T(ij)s are independent an...
متن کاملA Bayesian model for time-to-event data with informative censoring.
Randomized trials with dropouts or censored data and discrete time-to-event type outcomes are frequently analyzed using the Kaplan-Meier or product limit (PL) estimation method. However, the PL method assumes that the censoring mechanism is noninformative and when this assumption is violated, the inferences may not be valid. We propose an expanded PL method using a Bayesian framework to incorpo...
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ژورنال
عنوان ژورنال: Journal of the American Statistical Association
سال: 2001
ISSN: 0162-1459,1537-274X
DOI: 10.1198/016214501753209031