Bayesian modeling of embryonic growth using latent variables.

Bayesian modeling of embryonic growth using latent variables.
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使用潜在变量对胚胎生长进行贝叶斯建模。

DOI:
10.1093/biostatistics/kxm040
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发表时间:
2008
期刊:
Biostatistics (Oxford, England)
影响因子:
--
通讯作者:
Hartmann,KatherineE
Hartmann,KatherineE
中科院分区:
--
文献类型:
--
作者:
Slaughter,JamesC;Herring,AmyH;Hartmann,KatherineE

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In a growth model, individuals move progressively through a series of states in which each state is indicative of developmental status. Interest lies in estimating the rate of progression through each state while incorporating covariates that might affect the transition rates. We develop a Bayesian discrete-time multistate growth model for inference from cross-sectional data with unknown initiation times. For each subject, data are collected at only one time point at which we observe the state as well as covariates that measure developmental progress. We link the developmental progress variables to an underlying latent growth variable that can also affect the state transition rates. A subject with slow latent growth will then have relatively small developmental progress covariates and move through state transitions slowly. We then examine the association between latent growth and the probability of future events in a novel study of embryonic development and pregnancy loss. Using a Markov chain Monte Carlo (MCMC) algorithm for posterior computation, we found evidence in favor of a previously hypothesized but unproven association between slow growth early in pregnancy and increased risk of future spontaneous abortion.
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影响因子: 1.9
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DOI: --
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期刊: The Journal of biological chemistry
影响因子: --
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复合羟基二十碳四烯酸 (HETE) 的人 PMN 白细胞趋化活性。
DOI: --
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影响因子: 4.4
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