Empirical Bayesian Approach for Variance Component Model in Genetic Analysis of Psychological Disorder

2008 ◽  
Author(s):  
Hengqing Tong ◽  
Chao Yu ◽  
Xujie Zhao ◽  
Yang Liu
Keyword(s):  
Genetic Analysis ◽  
Bayesian Approach ◽  
Variance Component ◽  
Psychological Disorder ◽  
Component Model ◽  
Variance Component Model ◽  
Empirical Bayesian ◽  
Empirical Bayesian Approach

scholarly journals Genetic analysis of personality traits and alcoholism using a mixed discrete continuous trait variance component model

1999 ◽  
Vol 17 (S1) ◽  
pp. S121-S126 ◽  
Author(s):  
Stefan A. Czerwinski ◽  
Michael C. Mahaney ◽  
Jeff T. Williams ◽  
Laura Almasy ◽  
John Blangero
Keyword(s):  
Genetic Analysis ◽  
Personality Traits ◽  
Variance Component ◽  
Component Model ◽  
Variance Component Model ◽  
Continuous Trait ◽  
Trait Variance

scholarly journals An empirical Bayesian approach to incorporate directional movement information from a forage fish into the Arnason-Schwarz mark-recapture model

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Mary A. Bishop ◽  
Jordan W. Bernard
Keyword(s):  
Bayesian Approach ◽  
Gulf Of Alaska ◽  
Forage Fish ◽  
Pacific Herring ◽  
Prince William Sound ◽  
Modeling Framework ◽  
Empirical Bayesian ◽  
Directional Information ◽  
Directional Movement ◽  
Empirical Bayesian Approach

Abstract Background Over the past two decades, various species of forage fish have been successfully implanted with miniaturized acoustic transmitters and subsequently monitored using stationary acoustic receivers. When acoustic receivers are configured in an array, information related to fish direction can potentially be determined, depending upon the number and relative orientation of the acoustic receivers. However, it can be difficult to incorporate directional information into frequentist mark-recapture methods. Here we show how an empirical Bayesian approach can be used to develop a model that incorporates directional movement information into the Arnason-Schwarz modeling framework to describe survival and migration patterns of a Pacific herring (Clupea pallasii) population in coastal Alaska, USA. Methods We acoustic-tagged 326 adult Pacific herring during April 2017 and 2018 while on their spawning grounds in Prince William Sound Alaska, USA. To monitor their movements, stationary acoustic receivers were deployed at strategic locations throughout the Sound. Receivers located at the major entrances to the Gulf of Alaska were arranged in parallel arrays to determine the directional movements of the fish. Informative priors were used to incorporate the directional information recorded at the entrance arrays into the model. Results A seasonal migratory pattern was found at one of Prince William Sound’s major entrances to the Gulf of Alaska. At this entrance, fish tended to enter the Gulf of Alaska during spring and summer after spawning and return to Prince William Sound during the fall and winter. Fish mortality was higher during spring and summer than fall and winter in both Prince William Sound and the Gulf of Alaska. Conclusions An empirical Bayesian modeling approach can be used to extend the Arnason-Schwarz modeling framework to incorporate directional information from acoustic arrays to estimate survival and characterize the timing and direction of migratory movements of forage fish.

scholarly journals On the Best Quadratic Minimum Bias Non-Negative Estimator of a Two-Variance Component Model

2011 ◽  
Vol 1 (3) ◽  
pp. 280-285 ◽  
Author(s):  
Lars Sjöberg
Keyword(s):  
Variance Components ◽  
Variance Component ◽  
Component Model ◽  
Variance Component Model ◽  
Minimum Bias ◽  
Unbiased Estimators ◽  
Independent Observations ◽  
Special Case

On the Best Quadratic Minimum Bias Non-Negative Estimator of a Two-Variance Component ModelVariance components (VCs) in linear adjustment models are usually successfully computed by unbiased estimators. However, for many unbiased VC techniques estimated variance components might be negative, a result that cannot be tolerated by the user. This is, for example, the case with the simple additive VC model aσ2/1 + bσ2/2 with known coefficients a and b, where either of the unbiasedly estimated variance components σ2/1 + σ2/2 may frequently come out negative. This fact calls for so-called non-negative VC estimators. Here the Best Quadratic Minimum Bias Non-negative Estimator (BQMBNE) of a two-variance component model is derived. A special case with independent observations is explicitly presented.

scholarly journals An Empirical Bayesian Approach to Item Banking

1986 ◽  
Vol 10 (4) ◽  
pp. 345-354 ◽  
Author(s):  
Wim J. van der Linden ◽  
Theo J. H. M. Eggen
Keyword(s):  
Bayesian Approach ◽  
Empirical Bayesian ◽  
Empirical Bayesian Approach

scholarly journals An empirical bayesian approach for testing gene expression fold change and its application in detecting global dosage effects

2020 ◽  
Vol 2 (3) ◽  
Author(s):  
Zhenxing Guo ◽  
Ying Cui ◽  
Xiaowen Shi ◽  
James A Birchler ◽  
Igor Albizua ◽  
...  
Keyword(s):  
Gene Expression ◽  
Change Detection ◽  
Bayesian Approach ◽  
Variance Estimation ◽  
T Test ◽  
Fold Change ◽  
Empirical Bayesian ◽  
Biological Studies ◽  
Fold Change Detection ◽  
Empirical Bayesian Approach

Abstract We are motivated by biological studies intended to understand global gene expression fold change. Biologists have generally adopted a fixed cutoff to determine the significance of fold changes in gene expression studies (e.g. by using an observed fold change equal to two as a fixed threshold). Scientists can also use a t-test or a modified differential expression test to assess the significance of fold changes. However, these methods either fail to take advantage of the high dimensionality of gene expression data or fail to test fold change directly. Our research develops a new empirical Bayesian approach to substantially improve the power and accuracy of fold-change detection. Specifically, we more accurately estimate gene-wise error variation in the log of fold change. We then adopt a t-test with adjusted degrees of freedom for significance assessment. We apply our method to a dosage study in Arabidopsis and a Down syndrome study in humans to illustrate the utility of our approach. We also present a simulation study based on real datasets to demonstrate the accuracy of our method relative to error variance estimation and power in fold-change detection. Our developed R package with a detailed user manual is publicly available on GitHub at https://github.com/cuiyingbeicheng/Foldseq.

Hierarchical modeling of sequential behavioral data: An empirical Bayesian approach.

2002 ◽  
Vol 7 (2) ◽  
pp. 262-280 ◽  
Author(s):  
Getachew A. Dagne ◽  
George W. Howe ◽  
C. Hendricks Brown ◽  
Bengt O. Muthén
Keyword(s):  
Bayesian Approach ◽  
Hierarchical Modeling ◽  
Behavioral Data ◽  
Empirical Bayesian ◽  
Empirical Bayesian Approach
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