The Additive Risk Model for Estimation of Effect of Haplotype Match in BMT Studies |
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Authors: | THOMAS H SCHEIKE TORBEN MARTINUSSEN MEI‐JIE ZHANG |
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Institution: | 1. Department of Biostatistics, University of Copenhagen;2. Department of Biostatistics, University of Southern Denmark;3. Division of Biostatistics, Medical College of Wisconsin |
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Abstract: | Abstract. In this article we consider a problem from bone marrow transplant (BMT) studies where there is interest on assessing the effect of haplotype match for donor and patient on the overall survival. The BMT study we consider is based on donors and patients that are genotype matched, and this therefore leads to a missing data problem. We show how Aalen's additive risk model can be applied in this setting with the benefit that the time‐varying haplomatch effect can be easily studied. This problem has not been considered before, and the standard approach where one would use the expected‐maximization (EM) algorithm cannot be applied for this model because the likelihood is hard to evaluate without additional assumptions. We suggest an approach based on multivariate estimating equations that are solved using a recursive structure. This approach leads to an estimator where the large sample properties can be developed using product‐integration theory. Small sample properties are investigated using simulations in a setting that mimics the motivating haplomatch problem. |
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Keywords: | Aalen model additive risk model estimating equation flexible modelling haplomatch effects haplotype effects missing data semiparametric modelling survival data |
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