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Activity Number:
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330
- Advances in Time-to-Event and Survival Methods
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Type:
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Contributed
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Date/Time:
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Tuesday, August 9, 2022 : 2:00 PM to 3:50 PM
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Sponsor:
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Biometrics Section
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Abstract #322210
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Title:
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Regression Analysis of a Future State and Entry Time Distribution Conditional on a Past State in a Progressive Multistate Model with Right Censored Data
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Author(s):
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Yuting Yang* and Somnath Datta
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Companies:
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University of Florida and University of Florida
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Keywords:
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nonparametric;
fractional observation ;
multistate model;
competing risk techniques;
inverse weighting;
pseudo-value approach
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Abstract:
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We present a nonparametric method for estimating the conditional future state probabilities and distribution of state entry time conditional on a past state visit when data are subject to dependent censoring in a progressive multistate model where Markovity of the system is not assumed. These estimators are constructed using the competing risk techniques with risk sets consisting of fractional observations and inverse probability of censoring weights. The fractional observations correspond to estimates of the numbers of persons who ultimately enter a state from which the future state in question can be reached in 1 step. We then address the corresponding regression problem by combining these marginal estimators with the pseudo-value approach. Performance of our regression scheme is studied using a comprehensive simulation study. An analysis of a well known existing data on graft-versus-host disease for bone marrow transplant individuals presented using our novel methodology.
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Authors who are presenting talks have a * after their name.
