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Volumn 137, Issue 12 SPEC. ISS., 2007, Pages 3848-3858

A reanalysis of a longitudinal scleroderma clinical trial using non-ignorable missingness models

Author keywords

Bayesian inference; Gibbs sampler; Log score criterion; Selection models

Indexed keywords


EID: 34547895453     PISSN: 03783758     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jspi.2007.04.005     Document Type: Article
Times cited : (4)

References (52)
  • 1
    • 14144252238 scopus 로고    scopus 로고
    • A random effects transition model for longitudinal binary data with informative missingness
    • Albert P., and Follman D. A random effects transition model for longitudinal binary data with informative missingness. Statist. Neerlandica 57 (2003) 100-111
    • (2003) Statist. Neerlandica , vol.57 , pp. 100-111
    • Albert, P.1    Follman, D.2
  • 3
    • 34547901089 scopus 로고    scopus 로고
    • Best, N., Cowles, M., Vines, S., 1995. Coda: convergence diagnosis and output analysis software for Gibbs sampling output. Technical Report, MRC Biostatistics Unit, Cambridge.
  • 4
    • 0032273615 scopus 로고    scopus 로고
    • General methods for monitoring convergence of iterative simulations
    • Brooks S.P., and Gelman A. General methods for monitoring convergence of iterative simulations. J. Comput. Graphical Statist. 7 (1998) 434-455
    • (1998) J. Comput. Graphical Statist. , vol.7 , pp. 434-455
    • Brooks, S.P.1    Gelman, A.2
  • 5
    • 0037197598 scopus 로고    scopus 로고
    • Coping with missing data in clinical trials: a model-based approach applied to asthma trials
    • Carpenter J., Pocock S., and Lamm C.J. Coping with missing data in clinical trials: a model-based approach applied to asthma trials. Statist. Med. 21 (2002) 1043-1066
    • (2002) Statist. Med. , vol.21 , pp. 1043-1066
    • Carpenter, J.1    Pocock, S.2    Lamm, C.J.3
  • 8
    • 0033636008 scopus 로고    scopus 로고
    • Reparameterizing the pattern-mixture model for sensitivity analysis under informative dropout
    • Daniels M., and Hogan J. Reparameterizing the pattern-mixture model for sensitivity analysis under informative dropout. Biometrics 56 (2000) 1241-1248
    • (2000) Biometrics , vol.56 , pp. 1241-1248
    • Daniels, M.1    Hogan, J.2
  • 10
    • 0028627762 scopus 로고
    • Modeling the relationship between disease progression and survival time
    • De Gruttola V., and Tu X. Modeling the relationship between disease progression and survival time. Biometrics 50 (1994) 1003-1014
    • (1994) Biometrics , vol.50 , pp. 1003-1014
    • De Gruttola, V.1    Tu, X.2
  • 11
    • 0042066687 scopus 로고    scopus 로고
    • On the performance of rancom-coefficient pattern-mixture models for non-ignorable drop-out
    • Demirtas H., and Schafer J. On the performance of rancom-coefficient pattern-mixture models for non-ignorable drop-out. Statist. Med. 2 (2003) 2553-2575
    • (2003) Statist. Med. , vol.2 , pp. 2553-2575
    • Demirtas, H.1    Schafer, J.2
  • 13
    • 4243828610 scopus 로고
    • Informative drop-out in longitudinal data analysis
    • Diggle P., and Kenward M.G. Informative drop-out in longitudinal data analysis. Appl. Statist. 43 (1994) 49-73
    • (1994) Appl. Statist. , vol.43 , pp. 49-73
    • Diggle, P.1    Kenward, M.G.2
  • 14
    • 0347363890 scopus 로고    scopus 로고
    • Diagnostics for joint longitudinal and dropout time modeling
    • Dobson A., and Henderson R. Diagnostics for joint longitudinal and dropout time modeling. Biometrics 59 (2003) 741-751
    • (2003) Biometrics , vol.59 , pp. 741-751
    • Dobson, A.1    Henderson, R.2
  • 15
    • 34547888374 scopus 로고    scopus 로고
    • Draper, D., Krnjajic, M., 2005. Bayesian model specification. Technical Report, University of California, Santa Cruz.
  • 16
    • 0035044722 scopus 로고    scopus 로고
    • An alternative parameterization of the general linear mixture model for longitudinal data with non-ignorable dropouts
    • Fitzmaurice G., and Laird N. An alternative parameterization of the general linear mixture model for longitudinal data with non-ignorable dropouts. Statist. Med. 20 (2001) 1009-1021
    • (2001) Statist. Med. , vol.20 , pp. 1009-1021
    • Fitzmaurice, G.1    Laird, N.2
  • 17
    • 0029028456 scopus 로고
    • An approximate generalized linear model with random effects for informative missing data
    • Follman D., and Wu M. An approximate generalized linear model with random effects for informative missing data. Biometrics 51 (1995) 151-168
    • (1995) Biometrics , vol.51 , pp. 151-168
    • Follman, D.1    Wu, M.2
  • 19
    • 0001526195 scopus 로고
    • A predictive approach to model selection
    • Geisser S., and Eddy W. A predictive approach to model selection. J. Amer. Statist. Assoc. 74 (1979) 153-160
    • (1979) J. Amer. Statist. Assoc. , vol.74 , pp. 153-160
    • Geisser, S.1    Eddy, W.2
  • 20
    • 0000539315 scopus 로고
    • Bayesian model choice: asymptotics and exact calculations
    • Gelfand A.E., and Dey D.K. Bayesian model choice: asymptotics and exact calculations. J. Roy. Statist. Soc. Ser. B 56 (1994) 501-514
    • (1994) J. Roy. Statist. Soc. Ser. B , vol.56 , pp. 501-514
    • Gelfand, A.E.1    Dey, D.K.2
  • 21
    • 84867086419 scopus 로고    scopus 로고
    • Prior distributions for variance parameters in hierarchical models
    • Gelman A. Prior distributions for variance parameters in hierarchical models. Bayesian Anal. 1 (2006) 515-533
    • (2006) Bayesian Anal. , vol.1 , pp. 515-533
    • Gelman, A.1
  • 22
    • 84972492387 scopus 로고
    • Inference from iterative simulation using multiple sequences (with discussion)
    • Gelman A., and Rubin D.B. Inference from iterative simulation using multiple sequences (with discussion). Statist. Sci. 7 (1992) 457-511
    • (1992) Statist. Sci. , vol.7 , pp. 457-511
    • Gelman, A.1    Rubin, D.B.2
  • 26
    • 10844288743 scopus 로고    scopus 로고
    • A random pattern-mixture model for longitudinal data with dropouts
    • Guo W., Ratcliffe S., and Ten Have T. A random pattern-mixture model for longitudinal data with dropouts. J. Amer. Statist. Assoc. 99 (2004) 929-937
    • (2004) J. Amer. Statist. Assoc. , vol.99 , pp. 929-937
    • Guo, W.1    Ratcliffe, S.2    Ten Have, T.3
  • 27
    • 0002105479 scopus 로고    scopus 로고
    • Application of random-effects pattern-mixture models for missing data in longitudinal studies
    • Hedeker D., and Gibbons R. Application of random-effects pattern-mixture models for missing data in longitudinal studies. Psychol. Methods 2 (1997) 64-78
    • (1997) Psychol. Methods , vol.2 , pp. 64-78
    • Hedeker, D.1    Gibbons, R.2
  • 28
    • 0037507563 scopus 로고    scopus 로고
    • Missing responses in generalised linear mixed models when the missingness mechanism is nonignorable
    • Ibrahim J., Chen M.-H., and Lipsitz S. Missing responses in generalised linear mixed models when the missingness mechanism is nonignorable. Biometrika 88 (2001) 551-564
    • (2001) Biometrika , vol.88 , pp. 551-564
    • Ibrahim, J.1    Chen, M.-H.2    Lipsitz, S.3
  • 29
    • 0032534724 scopus 로고    scopus 로고
    • Selection models for repeated measurements with non-random dropout: an illustration of sensitivity
    • Kenward M.G. Selection models for repeated measurements with non-random dropout: an illustration of sensitivity. Statist. Med. 17 (1998) 2723-2732
    • (1998) Statist. Med. , vol.17 , pp. 2723-2732
    • Kenward, M.G.1
  • 30
    • 0020333131 scopus 로고
    • Random effects models for longitudinal data
    • Laird N.M., and Ware J.H. Random effects models for longitudinal data. Biometrics 38 (1982) 963-974
    • (1982) Biometrics , vol.38 , pp. 963-974
    • Laird, N.M.1    Ware, J.H.2
  • 31
    • 2942677478 scopus 로고    scopus 로고
    • Modeling longitudinal data with nonignorable dropouts using a latent dropout class model
    • Lin H., McCuloch C., and Rosenheck R. Modeling longitudinal data with nonignorable dropouts using a latent dropout class model. Biometrics 60 (2004) 295-305
    • (2004) Biometrics , vol.60 , pp. 295-305
    • Lin, H.1    McCuloch, C.2    Rosenheck, R.3
  • 32
    • 21144483152 scopus 로고
    • Pattern-mixture models for multivariate incomplete data
    • Little R. Pattern-mixture models for multivariate incomplete data. J. Amer. Statist. Assoc. 88 (1993) 125-134
    • (1993) J. Amer. Statist. Assoc. , vol.88 , pp. 125-134
    • Little, R.1
  • 33
    • 84950452119 scopus 로고
    • Modeling the drop-out mechanism in repeated-measures studies
    • Little R. Modeling the drop-out mechanism in repeated-measures studies. J. Amer. Statist. Assoc. 90 (1995) 1112-1121
    • (1995) J. Amer. Statist. Assoc. , vol.90 , pp. 1112-1121
    • Little, R.1
  • 35
    • 0037197628 scopus 로고    scopus 로고
    • Selection models and pattern-mixture models to analyse longitudinal quality of life data subject to drop-out
    • Michiels B., Molenberghs G., Bijnens L., Vangeneugden T., and Thijs H. Selection models and pattern-mixture models to analyse longitudinal quality of life data subject to drop-out. Statist. Med. 21 (2002) 1023-1041
    • (2002) Statist. Med. , vol.21 , pp. 1023-1041
    • Michiels, B.1    Molenberghs, G.2    Bijnens, L.3    Vangeneugden, T.4    Thijs, H.5
  • 36
    • 1842780226 scopus 로고    scopus 로고
    • Sensitivity analysis of longitudinal normal data with drop-outs
    • Minini P., and Chavance M. Sensitivity analysis of longitudinal normal data with drop-outs. Statist. Med. 23 (2004) 1039-1054
    • (2004) Statist. Med. , vol.23 , pp. 1039-1054
    • Minini, P.1    Chavance, M.2
  • 37
    • 28444468503 scopus 로고    scopus 로고
    • Sensitivity analysis of continous incomplete longitudinal outcomes
    • Molenberghs G., and Thijs H. Sensitivity analysis of continous incomplete longitudinal outcomes. Statist. Neerlandica 57 (2003) 112-135
    • (2003) Statist. Neerlandica , vol.57 , pp. 112-135
    • Molenberghs, G.1    Thijs, H.2
  • 40
    • 0346733311 scopus 로고    scopus 로고
    • Modeling longitudinal data with nonignorable dropouts using a latent dropout class model
    • Roy J. Modeling longitudinal data with nonignorable dropouts using a latent dropout class model. Biostatistics 59 (2003) 829-836
    • (2003) Biostatistics , vol.59 , pp. 829-836
    • Roy, J.1
  • 42
    • 2942658011 scopus 로고    scopus 로고
    • Incorporating prior beliefs about selection bias into the analysis of randomized trials with missing outcomes
    • Scharfstein D.O., Daniels M.J., and Robins J.M. Incorporating prior beliefs about selection bias into the analysis of randomized trials with missing outcomes. Biostatistics 4 (2003) 495-512
    • (2003) Biostatistics , vol.4 , pp. 495-512
    • Scharfstein, D.O.1    Daniels, M.J.2    Robins, J.M.3
  • 46
    • 13444302396 scopus 로고    scopus 로고
    • R2WinBUGS: a package for running WinBUGS from R
    • Sturtz S., Ligges U., and Gelman A. R2WinBUGS: a package for running WinBUGS from R. J. Statist. Software 12 3 (2005)
    • (2005) J. Statist. Software , vol.12 , Issue.3
    • Sturtz, S.1    Ligges, U.2    Gelman, A.3
  • 47
    • 0031944647 scopus 로고    scopus 로고
    • Mixed effects logistic regression models for longitudinal binary response data with informative drop-out
    • Ten Have T., Kunselman A., Pulkstenis E., and Landis J. Mixed effects logistic regression models for longitudinal binary response data with informative drop-out. Biometrics 54 (1998) 367-383
    • (1998) Biometrics , vol.54 , pp. 367-383
    • Ten Have, T.1    Kunselman, A.2    Pulkstenis, E.3    Landis, J.4
  • 49
    • 0039982650 scopus 로고    scopus 로고
    • Analysis of longitudinal data with non-ignorable non-monotone missing values
    • Troxel A., Harrington D., and Lipsitz S. Analysis of longitudinal data with non-ignorable non-monotone missing values. Appl. Statist. 47 (1998) 425-438
    • (1998) Appl. Statist. , vol.47 , pp. 425-438
    • Troxel, A.1    Harrington, D.2    Lipsitz, S.3
  • 51
    • 0023779040 scopus 로고
    • Analysis changes in the presence of informative right censoring caused by death and withdrawal
    • Wu M., and Bailey K. Analysis changes in the presence of informative right censoring caused by death and withdrawal. Statist. Med. 7 (1988) 337-346
    • (1988) Statist. Med. , vol.7 , pp. 337-346
    • Wu, M.1    Bailey, K.2
  • 52
    • 0023921412 scopus 로고
    • Estimation and comparison of changes in the presence of informative right censoring by modeling the censoring process
    • Wu M., and Carroll R. Estimation and comparison of changes in the presence of informative right censoring by modeling the censoring process. Biometrics 82 (1988) 175-188
    • (1988) Biometrics , vol.82 , pp. 175-188
    • Wu, M.1    Carroll, R.2


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