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Volumn 25, Issue 2, 2016, Pages 405-425

Parameter Expanded Algorithms for Bayesian Latent Variable Modeling of Genetic Pleiotropy Data

Author keywords

Bayesian inference; Latent variable; Marginal data augmentation; Markov chain Monte Carlo; Pleiotropy

Indexed keywords


EID: 84971422205     PISSN: 10618600     EISSN: 15372715     Source Type: Journal    
DOI: 10.1080/10618600.2014.988337     Document Type: Article
Times cited : (3)

References (32)
  • 5
    • 0033191404 scopus 로고    scopus 로고
    • Working Memory, Short-Term Memory, and General Fluid Intelligence: A Latent-Variable Approach
    • R.W.Engle,, S.W.Tuholski,, J.E.Laughlin,, A.R.A.Conway, (1999), Working Memory, Short-Term Memory, and General Fluid Intelligence: A Latent-Variable Approach, Journal of Experimental Psychology, 128, 309–331.
    • (1999) Journal of Experimental Psychology , vol.128 , pp. 309-331
    • Engle, R.W.1    Tuholski, S.W.2    Laughlin, J.E.3    Conway, A.R.A.4
  • 6
    • 50849118196 scopus 로고    scopus 로고
    • Markov Chain Monte Marlo: Can We Trust the Third Significant Figure?
    • J.Flegal,, M.Haran,, G.Jones, (2008), Markov Chain Monte Marlo: Can We Trust the Third Significant Figure?, Statistical Science, 23, 250–260.
    • (2008) Statistical Science , vol.23 , pp. 250-260
    • Flegal, J.1    Haran, M.2    Jones, G.3
  • 7
    • 0001574731 scopus 로고
    • Efficient Parametrisations for Normal Linear Mixed Models
    • A.E.Gelfand, (1995), Efficient Parametrisations for Normal Linear Mixed Models, Biometrika, 82, 479–488.
    • (1995) Biometrika , vol.82 , pp. 479-488
    • Gelfand, A.E.1
  • 8
    • 84867086419 scopus 로고    scopus 로고
    • Prior Distributions for Variance Parameters in Hierarchical Models
    • A.E.Gelfand, (2006), Prior Distributions for Variance Parameters in Hierarchical Models, Bayesian Analysis, 1, 515–533.
    • (2006) Bayesian Analysis , vol.1 , pp. 515-533
    • Gelfand, A.E.1
  • 9
    • 0000736067 scopus 로고    scopus 로고
    • Simulating Normalizing Constants: From Importance Sampling to Bridge Sampling to Path Sampling
    • A.Gelman,, X.-L.Meng, (1998), Simulating Normalizing Constants: From Importance Sampling to Bridge Sampling to Path Sampling, Statistical Science, 13, 163–185.
    • (1998) Statistical Science , vol.13 , pp. 163-185
    • Gelman, A.1    Meng, X.-L.2
  • 10
    • 84972492387 scopus 로고
    • Inference from Iterative Simulation Using Multiple Sequences” (with discussion)
    • A.Gelman,, and D.B.Rubin, (1992), “Inference from Iterative Simulation Using Multiple Sequences” (with discussion), Statistical Science, 457–511.
    • (1992) Statistical Science , pp. 457-511
    • Gelman, A.1    Rubin, D.B.2
  • 12
    • 84972511893 scopus 로고
    • Practical Markov Chain Monte Carlo” (with discussion)
    • C.J.Geyer, (1992), Practical Markov Chain Monte Carlo” (with discussion), Statistical Science, 7, 473–483.
    • (1992) Statistical Science , vol.7 , pp. 473-483
    • Geyer, C.J.1
  • 13
    • 72649086818 scopus 로고    scopus 로고
    • Default Prior Distributions and Efficient Posterior Computation in Bayesian Factor Analysis
    • J.Ghosh,, D.B.Dunson, (2009), Default Prior Distributions and Efficient Posterior Computation in Bayesian Factor Analysis, Journal of Computational and Graphical Statistics, 18, 306–320.
    • (2009) Journal of Computational and Graphical Statistics , vol.18 , pp. 306-320
    • Ghosh, J.1    Dunson, D.B.2
  • 14
    • 34547835365 scopus 로고    scopus 로고
    • A Theoretical Comparison of the Data Augmentation, Marginal Augmentation and PX-DA Algorithms
    • J.P.Hobert,, D.Marchev, (2008), A Theoretical Comparison of the Data Augmentation, Marginal Augmentation and PX-DA Algorithms, Annals of Statistics, 36, 532–554.
    • (2008) Annals of Statistics , vol.36 , pp. 532-554
    • Hobert, J.P.1    Marchev, D.2
  • 15
    • 84923681567 scopus 로고    scopus 로고
    • Specification of Generalized Linear Mixed Models for Family Data using Markov Chain Monte Carlo Methods
    • K.M.Jamsen,, S.G.Zaloumis,, K.J.Scurrah,, and L.C.Gurrin, (2010), “Specification of Generalized Linear Mixed Models for Family Data using Markov Chain Monte Carlo Methods,” Journal of Biometrics and Biostatistics, S1–003.
    • (2010) Journal of Biometrics and Biostatistics , pp. S1-S003
    • Jamsen, K.M.1    Zaloumis, S.G.2    Scurrah, K.J.3    Gurrin, L.C.4
  • 16
    • 84890222725 scopus 로고    scopus 로고
    • Robust Rare Variant Association Testing for Quantitative Traits in Samples With Related Individuals
    • D.Jiang,, M.S.McPeek, (2014), Robust Rare Variant Association Testing for Quantitative Traits in Samples With Related Individuals, Genetic Epidemiology, 38, 10–20.
    • (2014) Genetic Epidemiology , vol.38 , pp. 10-20
    • Jiang, D.1    McPeek, M.S.2
  • 17
    • 67650315212 scopus 로고    scopus 로고
    • Analysis of Childhood Morbidity With Geoadditive Probit and Latent Variable Model: A Case Study for Egypt
    • K.Khatab,, L.Fahrmeir, (2009), Analysis of Childhood Morbidity With Geoadditive Probit and Latent Variable Model: A Case Study for Egypt, The American Journal of Tropical Medicine and Hygiene, 81, 116–128.
    • (2009) The American Journal of Tropical Medicine and Hygiene , vol.81 , pp. 116-128
    • Khatab, K.1    Fahrmeir, L.2
  • 18
    • 84952173852 scopus 로고
    • Estimating Potential Output as a Latent Variable
    • K.N.Kuttner, (1994), Estimating Potential Output as a Latent Variable, Journal of Business and Economic Studies, 12, 361–368.
    • (1994) Journal of Business and Economic Studies , vol.12 , pp. 361-368
    • Kuttner, K.N.1
  • 19
    • 2242448298 scopus 로고    scopus 로고
    • Bayesian Selection on the Number of Factors in a Factor Analysis Model
    • S.Y.Lee,, X.Y.Song, (2002), Bayesian Selection on the Number of Factors in a Factor Analysis Model, Behaviormetrika, 29, 23–40.
    • (2002) Behaviormetrika , vol.29 , pp. 23-40
    • Lee, S.Y.1    Song, X.Y.2
  • 21
    • 0000761884 scopus 로고    scopus 로고
    • Seeking Efficient Data Augmentation Schemes via Conditional and Marginal Augmentation
    • X.-L.Meng,, D.van Dyk, (1999), Seeking Efficient Data Augmentation Schemes via Conditional and Marginal Augmentation, Biometrika, 86, 301–320.
    • (1999) Biometrika , vol.86 , pp. 301-320
    • Meng, X.-L.1    van Dyk, D.2
  • 22
    • 77449128370 scopus 로고    scopus 로고
    • A Genome-Wide Association Study Identifies a Novel Major Locus for Glycemic Control in Type 1 Diabetes, as Measured by Both A1C and Glucose
    • Paterson, A. D., Waggott, D., Boright, A. P, Hosseini, S. M., Shen, E., Sylvestre, M.-P., Wong, I., Bharaj, B., Cleary, P. A., Lachin, J. M., MAGIC (Meta-Analyses of Glucose and Insulin-related traits Consortium), Below, J. E., Nicolae, D., Cox, N. J., Canty, A. J., Sun, L., Bull, S. B. and the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications Research Group
    • Paterson, A. D., Waggott, D., Boright, A. P, Hosseini, S. M., Shen, E., Sylvestre, M.-P., Wong, I., Bharaj, B., Cleary, P. A., Lachin, J. M., MAGIC (Meta-Analyses of Glucose and Insulin-related traits Consortium), Below, J. E., Nicolae, D., Cox, N. J., Canty, A. J., Sun, L., Bull, S. B. and the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications Research Group (2010), A Genome-Wide Association Study Identifies a Novel Major Locus for Glycemic Control in Type 1 Diabetes, as Measured by Both A1C and Glucose, Diabetes, 59, 539–549.
    • (2010) Diabetes , vol.59 , pp. 539-549
  • 23
    • 0033636129 scopus 로고    scopus 로고
    • Latent Variable Models for Longitudinal Data With Multiple Continuous Outcomes
    • J.Roy,, X.Lin, (2000), Latent Variable Models for Longitudinal Data With Multiple Continuous Outcomes, Biometrics, 56, 1047–1054.
    • (2000) Biometrics , vol.56 , pp. 1047-1054
    • Roy, J.1    Lin, X.2
  • 24
    • 0029938347 scopus 로고    scopus 로고
    • Latent Variable Models with Fixed Effects
    • M.D.Sammel,, L.M.Ryan, (1996), Latent Variable Models with Fixed Effects, Biometrics, 52, 650–663.
    • (1996) Biometrics , vol.52 , pp. 650-663
    • Sammel, M.D.1    Ryan, L.M.2
  • 25
    • 0001571385 scopus 로고    scopus 로고
    • Latent Variable Models for Mixed Discrete and Continuous Outcomes
    • M.D.Sammel, (1997), Latent Variable Models for Mixed Discrete and Continuous Outcomes, Journal of the Royal Statistical Society, Series B, 59, 667–678.
    • (1997) Journal of the Royal Statistical Society, Series B , vol.59 , pp. 667-678
    • Sammel, M.D.1
  • 28
  • 29
    • 76049108917 scopus 로고    scopus 로고
    • ROADTRIPS: Case-Control Association Testing With Partially or Completely Unknown Population and Pedigree Structure
    • T.Thornton,, M.S.McPeek, (2010), ROADTRIPS: Case-Control Association Testing With Partially or Completely Unknown Population and Pedigree Structure, The American Journal of Human Genetics, 86, 172–184.
    • (2010) The American Journal of Human Genetics , vol.86 , pp. 172-184
    • Thornton, T.1    McPeek, M.S.2
  • 32
    • 84971437531 scopus 로고    scopus 로고
    • A Repeated Measures Genome wide Association Study of Blood Pressure in Type 1 Diabetes
    • Abstract # 203 Presented at the Nineteenth Annual Meeting of the International Genetic Epidemiology Society
    • C.Ye,, A.J.Canty,, D.Waggott,, M.-P.Sylvestre,, E.Shen,, M.Hosseini,, (2010), A Repeated Measures Genome wide Association Study of Blood Pressure in Type 1 Diabetes,” Abstract # 203 Presented at the Nineteenth Annual Meeting of the International Genetic Epidemiology Society, Genetic Epidemiology, 34, 973.
    • (2010) Genetic Epidemiology , vol.34 , pp. 973
    • Ye, C.1    Canty, A.J.2    Waggott, D.3    Sylvestre, M.-P.4    Shen, E.5    Hosseini, M.6


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.