메뉴 건너뛰기




Volumn 39, Issue 5, 2014, Pages 307-332

Modeling heterogeneous variance–Covariance components in two-level models

Author keywords

Heterogeneous within group variances; Heteroscedasticity; Log linear variance models; Multilevel models; Variance functions

Indexed keywords


EID: 84908893395     PISSN: 10769986     EISSN: 19351054     Source Type: Journal    
DOI: 10.3102/1076998614546494     Document Type: Article
Times cited : (63)

References (50)
  • 1
    • 0023586174 scopus 로고
    • Modelling variance heterogeneity in normal regression using GLIM
    • Aitkin, M.Modelling variance heterogeneity in normal regression using GLIM.Applied Statistics. 1987;36:332-339
    • (1987) Applied Statistics , vol.36 , pp. 332-339
    • Aitkin, M.1
  • 2
    • 0032958330 scopus 로고    scopus 로고
    • A general maximum likelihood analysis of variance components in generalized linear models
    • Aitkin, M.A general maximum likelihood analysis of variance components in generalized linear models.Biometrics. 1999;55:117-128
    • (1999) Biometrics , vol.55 , pp. 117-128
    • Aitkin, M.1
  • 4
    • 30144445854 scopus 로고    scopus 로고
    • MCMC algorithms for constrained variance matrices
    • Browne, W. J.MCMC algorithms for constrained variance matrices.Computational Statistics & Data Analysis. 2006;50:1655-1677
    • (2006) Computational Statistics & Data Analysis , vol.50 , pp. 1655-1677
    • Browne, W.J.1
  • 5
    • 0034394761 scopus 로고    scopus 로고
    • Implementation and performance issues in the Bayesian and likelihood fitting of multilevel models
    • Browne, W. J.,Draper, D.Implementation and performance issues in the Bayesian and likelihood fitting of multilevel models.Computational Statistics. 2000;15:391-420
    • (2000) Computational Statistics , vol.15 , pp. 391-420
    • Browne, W.J.1    Draper, D.2
  • 7
    • 84908889663 scopus 로고    scopus 로고
    • Stat-JR version 1.0. Centre for Multilevel Modelling, University of Bristol & Electronics and Computer Science, University of Southampton
    • CharltonC. M. J.MichaelidesD. T.ParkerR. M. A.CameronB.SzmaragdC.YangH.…BrowneW. J
    • CharltonC. M. J.MichaelidesD. T.ParkerR. M. A.CameronB.SzmaragdC.YangH.…BrowneW. J. (2013). Stat-JR version 1.0. Centre for Multilevel Modelling, University of Bristol & Electronics and Computer Science, University of Southampton. Retrieved fromhttp://www.bristol.ac.uk/cmm/software/statjr/
    • (2013) Retrieved from
  • 11
    • 0003445439 scopus 로고    scopus 로고
    • 2011). Multilevel statistical models (4th ed.). Chichester, England: John Wiley.Chichester, England: ; :, John Wiley
    • Goldstein, H.Multilevel statistical models. 2011. Multilevel statistical models (4th ed.). Chichester, England: John Wiley.Chichester, England: John Wiley; 2011:
    • (2011) Multilevel statistical models
    • Goldstein, H.1
  • 14
    • 0001008891 scopus 로고
    • Estimating regression models with multiplication heteroskedasticity
    • Harvey, A.Estimating regression models with multiplication heteroskedasticity.Econometrica. 1976;44:461-465
    • (1976) Econometrica , vol.44 , pp. 461-465
    • Harvey, A.1
  • 16
    • 43749100899 scopus 로고    scopus 로고
    • An application of a mixed-effects location scale model for analysis of ecological momentary assessment (EMA) data
    • Hedeker, D.,Mermelstein, R. J.,Demirtas, H.An application of a mixed-effects location scale model for analysis of ecological momentary assessment (EMA) data.Biometrics. 2008;64:627-634
    • (2008) Biometrics , vol.64 , pp. 627-634
    • Hedeker, D.1    Mermelstein, R.J.2    Demirtas, H.3
  • 17
    • 84875166129 scopus 로고    scopus 로고
    • MIXREGLS: A fortran program for mixed-effects location scale analysis
    • Hedeker, D.,Nordgren, R.MIXREGLS: A fortran program for mixed-effects location scale analysis.Journal of Statistical Software. 2013;52:1-38
    • (2013) Journal of Statistical Software , vol.52 , pp. 1-38
    • Hedeker, D.1    Nordgren, R.2
  • 19
    • 0032359236 scopus 로고    scopus 로고
    • Application of Gibbs sampling to nested variance components models with heterogeneous within-group variance
    • Kasim, R. M.,Raudenbush, S. W.Application of Gibbs sampling to nested variance components models with heterogeneous within-group variance.Journal of Educational and Behavioral Statistics. 1998;23:93-116
    • (1998) Journal of Educational and Behavioral Statistics , vol.23 , pp. 93-116
    • Kasim, R.M.1    Raudenbush, S.W.2
  • 20
    • 63349083543 scopus 로고    scopus 로고
    • Closing the gap: Modeling within-school variance heterogeneity in school effect studies
    • Kim, J.,Choi, K.Closing the gap: Modeling within-school variance heterogeneity in school effect studies.Asia Pacific Education Review. 2008;9:206-220
    • (2008) Asia Pacific Education Review , vol.9 , pp. 206-220
    • Kim, J.1    Choi, K.2
  • 21
    • 79958824438 scopus 로고    scopus 로고
    • Examining heterogeneity in residual variance to detect differential response to treatments
    • Kim, J.,Seltzer, M.Examining heterogeneity in residual variance to detect differential response to treatments.Psychological Methods. 2011;16:192-208
    • (2011) Psychological Methods , vol.16 , pp. 192-208
    • Kim, J.1    Seltzer, M.2
  • 22
    • 84961863091 scopus 로고    scopus 로고
    • runmixregls—A Program to run the MIXREGLS mixed-effects location scale software from within Stata
    • Leckie, G.runmixregls—A Program to run the MIXREGLS mixed-effects location scale software from within Stata.Journal of Statistical Software. 2014;59:1-41
    • (2014) Journal of Statistical Software , vol.59 , pp. 1-41
    • Leckie, G.1
  • 23
    • 84055198279 scopus 로고    scopus 로고
    • Rater effects on essay scoring: A multilevel analysis of severity drift, central tendency, and rater experience
    • Leckie, G.,Baird, J. A.Rater effects on essay scoring: A multilevel analysis of severity drift, central tendency, and rater experience.Journal of Educational Measurement. 2011;48:399-418
    • (2011) Journal of Educational Measurement , vol.48 , pp. 399-418
    • Leckie, G.1    Baird, J.A.2
  • 24
    • 84920999169 scopus 로고    scopus 로고
    • A multilevel modelling approach to measuring changing patterns of ethnic composition and segregation among London secondary schools, 2001-2010
    • Leckie, G.,Goldstein, H.A multilevel modelling approach to measuring changing patterns of ethnic composition and segregation among London secondary schools, 2001-2010.Journal of the Royal Statistical Society: Series A (Statistics in Society). 2014;:
    • (2014) Journal of the Royal Statistical Society: Series A (Statistics in Society)
    • Leckie, G.1    Goldstein, H.2
  • 27
    • 0012342630 scopus 로고    scopus 로고
    • Hierarchical generalised linear models: A synthesis of generalised linear models, random-effect models and structured dispersions
    • Lee, Y.,Nelder, J. A.Hierarchical generalised linear models: A synthesis of generalised linear models, random-effect models and structured dispersions.Biometrika. 2001;88:987-1006
    • (2001) Biometrika , vol.88 , pp. 987-1006
    • Lee, Y.1    Nelder, J.A.2
  • 28
    • 33644629431 scopus 로고    scopus 로고
    • Double hierarchical generalized linear models (with discussion)
    • Lee, Y.,Nelder, J. A.Double hierarchical generalized linear models (with discussion).Applied Statistics. 2006;55:139-185
    • (2006) Applied Statistics , vol.55 , pp. 139-185
    • Lee, Y.1    Nelder, J.A.2
  • 32
    • 0006407254 scopus 로고    scopus 로고
    • WinBUGS—A Bayesian modelling framework: Concepts, structure, and extensibility
    • Lunn, D. J.,Thomas, A.,Best, N.,Spiegelhalter, D.WinBUGS—A Bayesian modelling framework: Concepts, structure, and extensibility.Statistics and Computing. 2000;10:325-337
    • (2000) Statistics and Computing , vol.10 , pp. 325-337
    • Lunn, D.J.1    Thomas, A.2    Best, N.3    Spiegelhalter, D.4
  • 33
    • 79952602238 scopus 로고    scopus 로고
    • Prediction of random effects in linear and generalized linear models under model misspecification
    • McCulloch, C. E.,Neuhaus, J. M.Prediction of random effects in linear and generalized linear models under model misspecification.Biometrics. 2011;67:270-279
    • (2011) Biometrics , vol.67 , pp. 270-279
    • McCulloch, C.E.1    Neuhaus, J.M.2
  • 34
    • 84908889662 scopus 로고    scopus 로고
    • Package ‘dhglm’: Double hierarchical generalized linear models
    • NohM.LeeY
    • NohM.LeeY. (2013). Package ‘dhglm’: Double hierarchical generalized linear models. Retrieved fromhttp://CRAN.R-project.org/package=dhglm
    • (2013) Retrieved from
  • 36
    • 84908889661 scopus 로고    scopus 로고
    • MLwiN Version 2.1. Centre for Multilevel Modelling, University of Bristol, England
    • RasbashJ.CharltonC.BrowneW. J.HealyM.CameronB
    • RasbashJ.CharltonC.BrowneW. J.HealyM.CameronB. (2009). MLwiN Version 2.1. Centre for Multilevel Modelling, University of Bristol, England. Retrieved fromhttp://www.mlwin.com
    • (2009) Retrieved fromhttp://www.mlwin.com
  • 37
    • 84859584761 scopus 로고    scopus 로고
    • Modeling individual differences in within-person variation of negative and positive affect in a mixed effects location scale model using BUGS/JAGS
    • Rast, P.,Hofer, S. M.,Sparks, C.Modeling individual differences in within-person variation of negative and positive affect in a mixed effects location scale model using BUGS/JAGS.Multivariate Behavioral Research. 2012;47:177-200
    • (2012) Multivariate Behavioral Research , vol.47 , pp. 177-200
    • Rast, P.1    Hofer, S.M.2    Sparks, C.3
  • 38
    • 84936526615 scopus 로고
    • A hierarchical model for studying school effects
    • Raudenbush, S.,Bryk, A. S.A hierarchical model for studying school effects.Sociology of Education. 1986;59:1-17
    • (1986) Sociology of Education , vol.59 , pp. 1-17
    • Raudenbush, S.1    Bryk, A.S.2
  • 40
    • 0003967354 scopus 로고    scopus 로고
    • 2002). Hierarchical linear models: Applications and data analysis methods (2nd ed.). Thousand Oaks, CA: Sage.Thousand Oaks, CA: ; :, Sage
    • Raudenbush, S. W.,Bryk, A. S.Hierarchical linear models: Applications and data analysis methods. 2002. Hierarchical linear models: Applications and data analysis methods (2nd ed.). Thousand Oaks, CA: Sage.Thousand Oaks, CA: Sage; 2002:
    • (2002) Hierarchical linear models: Applications and data analysis methods
    • Raudenbush, S.W.1    Bryk, A.S.2
  • 44
    • 84883634267 scopus 로고    scopus 로고
    • 2013). Base SAS 9.3 procedures guide. Statistical procedures (2nd ed.). Cary, NC: SAS Institute Inc. Retrieved fromhttp://www.sas.com/Cary, NC: ; :, SAS Institute Inc
    • Base SAS 9.3 procedures guide. Statistical procedures. 2013. Base SAS 9.3 procedures guide. Statistical procedures (2nd ed.). Cary, NC: SAS Institute Inc. Retrieved fromhttp://www.sas.com/Cary, NC: SAS Institute Inc; 2013:
    • (2013) Base SAS 9.3 procedures guide. Statistical procedures
  • 50
    • 84988123007 scopus 로고
    • A longitudinal hierarchical linear model for estimating school effects and their stability
    • Willms, J. D.,Raudenbush, S. W.A longitudinal hierarchical linear model for estimating school effects and their stability.Journal of Educational Measurement. 1989;26:209-232
    • (1989) Journal of Educational Measurement , vol.26 , pp. 209-232
    • Willms, J.D.1    Raudenbush, S.W.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.