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Volumn 58, Issue 4, 2002, Pages 989-996

A pattern-mixture model for longitudinal binary responses with nonignorable nonresponse

Author keywords

Longitudinal data; Missing data; Nonignorable; Pattern mixture model; Repeated measures

Indexed keywords

BINARY RESPONSE; LONGITUDINAL DATA; LONGITUDINAL STUDY; MISSING DATA; MISSING RESPONSE; MIXTURE MODELING; NONIGNORABLE; NONIGNORABLE NONRESPONSE; PATTERN-MIXTURE MODEL; REPEATED MEASURES;

EID: 0036971533     PISSN: 0006341X     EISSN: None     Source Type: Journal    
DOI: 10.1111/j.0006-341X.2002.00989.x     Document Type: Review
Times cited : (20)

References (41)
  • 1
    • 0002881703 scopus 로고
    • A representation of the joint distribution of responses to n dichotomous items
    • H. Solomon (ed). Stanford, California: Stanford University Press
    • Bahadur, R. R. (1961). A representation of the joint distribution of responses to n dichotomous items. In Studies in Item Analysis and Prediction, H. Solomon (ed), 158-168. Stanford, California: Stanford University Press.
    • (1961) Studies in Item Analysis and Prediction , pp. 158-168
    • Bahadur, R.R.1
  • 2
    • 0027717182 scopus 로고
    • Marginal modeling of binary cross-over data
    • Becker, M. P. and Balagtas, C. C. (1993). Marginal modeling of binary cross-over data. Biometrics 49, 997-1009.
    • (1993) Biometrics , vol.49 , pp. 997-1009
    • Becker, M.P.1    Balagtas, C.C.2
  • 3
    • 0033636008 scopus 로고    scopus 로고
    • Reparameterizing the pattern-mixture model for sensitivity analyses under informative dropout
    • Daniels, M. and Hogan, J. W. (2000). Reparameterizing the pattern-mixture model for sensitivity analyses under informative dropout. Biometrics 56, 1241-1248.
    • (2000) Biometrics , vol.56 , pp. 1241-1248
    • Daniels, M.1    Hogan, J.W.2
  • 4
    • 4243828610 scopus 로고
    • Informative drop-out in longitudinal data analysis
    • Diggle, P. and Kenward, M. G. (1994). Informative drop-out in longitudinal data analysis. Applied Statistics 43, 49-93.
    • (1994) Applied Statistics , vol.43 , pp. 49-93
    • Diggle, P.1    Kenward, M.G.2
  • 5
    • 0012832257 scopus 로고
    • Fitting regression models to a multivariate binary response
    • G. Rosenqvist, K. Juselius, K. Nordström, and J. Palmgren (eds). Helsinki: Swedish School of Economics and Business Administration
    • Ekholm, A. (1991). Fitting regression models to a multivariate binary response. In A Spectrum of Statistical Thought: Essays in Statistical Theory, Economics, and Population Genetics in Honour of Johan Fellman, G. Rosenqvist, K. Juselius, K. Nordström, and J. Palmgren (eds), 19-32. Helsinki: Swedish School of Economics and Business Administration.
    • (1991) A Spectrum of Statistical Thought: Essays in Statistical Theory, Economics, and Population Genetics in Honour of Johan Fellman , pp. 19-32
    • Ekholm, A.1
  • 6
    • 0041175330 scopus 로고    scopus 로고
    • The Muscatine children's obesity data reanalysed using pattern mixture models
    • Ekholm, A. and Skinner, C. (1998). The Muscatine children's obesity data reanalysed using pattern mixture models. Applied Statistics 47, 251-263.
    • (1998) Applied Statistics , vol.47 , pp. 251-263
    • Ekholm, A.1    Skinner, C.2
  • 7
    • 0000851762 scopus 로고
    • Marginal regression analysis of a multivariate binary response
    • Ekholm, A., Smith, P. W. F., and McDonald, J. W. (1995). Marginal regression analysis of a multivariate binary response. Biometrika 82, 847-854.
    • (1995) Biometrika , vol.82 , pp. 847-854
    • Ekholm, A.1    Smith, P.W.F.2    McDonald, J.W.3
  • 8
    • 0003289748 scopus 로고    scopus 로고
    • Regression models for discrete longitudinal responses
    • B. Everitt and G. Dunn (eds). London: Arnold
    • Fitzmaurice, G. M. (1998). Regression models for discrete longitudinal responses. In Statistical Analysis of Medical Data: New Developments, B. Everitt and G. Dunn (eds), 175-201. London: Arnold.
    • (1998) Statistical Analysis of Medical Data: New Developments , pp. 175-201
    • Fitzmaurice, G.M.1
  • 9
    • 0001216089 scopus 로고    scopus 로고
    • Generalized linear mixture models for handling nonignorable dropouts in longitudinal studies
    • Fitzmaurice, G, M. and Laird, N. M. (2000), Generalized linear mixture models for handling nonignorable dropouts in longitudinal studies. Biostatistics 1, 141-156.
    • (2000) Biostatistics , vol.1 , pp. 141-156
    • Fitzmaurice, G.1    Laird, M.N.M.2
  • 13
    • 0029028456 scopus 로고
    • An approximate generalized linear model with random effects for informative missing data
    • Follmann, D. and Wu, M. (1995). An approximate generalized linear model with random effects for informative missing data. Biometrics 51, 151-168.
    • (1995) Biometrics , vol.51 , pp. 151-168
    • Follmann, D.1    Wu, M.2
  • 15
    • 0031032359 scopus 로고    scopus 로고
    • Mixture models for the joint distribution of repeated measures and event times
    • Hogan, J. and Laird, N. M. (1997), Mixture models for the joint distribution of repeated measures and event times. Statistics in Medicine 16, 239-258.
    • (1997) Statistics in Medicine , vol.16 , pp. 239-258
    • Hogan, J.1    Laird, N.M.2
  • 16
    • 0023716933 scopus 로고
    • Missing data in longitudinal studies
    • Laird, N. M. (1988). Missing data in longitudinal studies. Statistics in Medicine 7, 305-315.
    • (1988) Statistics in Medicine , vol.7 , pp. 305-315
    • Laird, N.M.1
  • 17
    • 0020333131 scopus 로고
    • Random-effects models for longitudinal data
    • Laird, N. M. and Ware, J. H. (1982). Random-effects models for longitudinal data. Biometrics 38, 963-974.
    • (1982) Biometrics , vol.38 , pp. 963-974
    • Laird, N.M.1    Ware, J.H.2
  • 19
    • 0025633264 scopus 로고
    • Maximum likelihood regression methods for paired binary data
    • Lipsitz, S. R., Laird, N. M., and Harrington, D. P. (1990). Maximum likelihood regression methods for paired binary data. Statistics in Medicine 9, 1517-1525.
    • (1990) Statistics in Medicine , vol.9 , pp. 1517-1525
    • Lipsitz, S.R.1    Laird, N.M.2    Harrington, D.P.3
  • 21
    • 77956890002 scopus 로고
    • A class of pattern-mixture models for normal incomplete data
    • Little, R. J. A. (1994). A class of pattern-mixture models for normal incomplete data. Biometrika 88, 471-483.
    • (1994) Biometrika , vol.88 , pp. 471-483
    • Little, R.J.A.1
  • 23
    • 0029995115 scopus 로고    scopus 로고
    • Pattern-mixture models for multivariate incomplete data with covariates
    • Little, R. J. A. and Wang, Y. (1996). Pattern-mixture models for multivariate incomplete data with covariates. Biometrics 52, 98-111.
    • (1996) Biometrics , vol.52 , pp. 98-111
    • Little, R.J.A.1    Wang, Y.2
  • 26
    • 0032885858 scopus 로고    scopus 로고
    • Selection models and pattern-mixture models for incomplete data with covariates
    • Michiels, B., Molenberghs, G., and Lipsitz, S. R. (1999b). Selection models and pattern-mixture models for incomplete data with covariates. Biometrics 55, 978-983.
    • (1999) Biometrics , vol.55 , pp. 978-983
    • Michiels, B.1    Molenberghs, G.2    Lipsitz, S.R.3
  • 27
    • 0001986642 scopus 로고    scopus 로고
    • The analysis of longitudinal ordinal data with nonrandom drop-out
    • Molenberghs, G., Kenward, M. G., and Lesaffre, E. (1997). The analysis of longitudinal ordinal data with nonrandom drop-out. Biometrika 84, 33-44.
    • (1997) Biometrika , vol.84 , pp. 33-44
    • Molenberghs, G.1    Kenward, M.G.2    Lesaffre, E.3
  • 28
    • 0032353609 scopus 로고    scopus 로고
    • Pseudo-likelihood for combined selection and patternmixture models for incomplete data
    • Molenberghs, G., Michiels, B., and Kenward, M. G. (1998a). Pseudo-likelihood for combined selection and patternmixture models for incomplete data. Biometrical Journal 40, 557-572.
    • (1998) Biometrical Journal , vol.40 , pp. 557-572
    • Molenberghs, G.1    Michiels, B.2    Kenward, M.G.3
  • 30
    • 0033571770 scopus 로고    scopus 로고
    • Simple pattern-mixture models for longitudinal data with missing observations: Analysis of urinary incontinence data
    • Park, T. and Lee, S.-Y. (1999). Simple pattern-mixture models for longitudinal data with missing observations: Analysis of urinary incontinence data. Statistics in Medicine 18, 2933-2941.
    • (1999) Statistics in Medicine , vol.18 , pp. 2933-2941
    • Park, T.1    Lee, S.-Y.2
  • 31
    • 84950421496 scopus 로고
    • Analysis of semiparametric regression models for repeated outcomes in the presence of missing data
    • Robins, J. M., Rotnitzky, A., and Zhao, L. P. (1995). Analysis of semiparametric regression models for repeated outcomes in the presence of missing data. Journal of the American Statistical Association 90, 106-121.
    • (1995) Journal of the American Statistical Association , vol.90 , pp. 106-121
    • Robins, J.M.1    Rotnitzky, A.2    Zhao, L.P.3
  • 32
    • 0031014354 scopus 로고    scopus 로고
    • Analysis of semi-parametric regression models with non-ignorable non-response
    • Rotnitzky, A. and Robins, J. (1997). Analysis of semi-parametric regression models with non-ignorable non-response. Statistics in Medicine 16, 81-102.
    • (1997) Statistics in Medicine , vol.16 , pp. 81-102
    • Rotnitzky, A.1    Robins, J.2
  • 34
    • 0017133178 scopus 로고
    • Inference and missing data
    • Rubin, D. B. (1976). Inference and missing data. Biometrika 63, 581-592.
    • (1976) Biometrika , vol.63 , pp. 581-592
    • Rubin, D.B.1
  • 35
    • 0031944647 scopus 로고    scopus 로고
    • Mixed effects logistic regression models for longitudinal binary response data with informative drop-out
    • Ten Have, T. R., Kunselman, A. R., Pulkstenis, E. P., and Landis, J. R. (1998). Mixed effects logistic regression models for longitudinal binary response data with informative drop-out. Biometrics 54, 367-383.
    • (1998) Biometrics , vol.54 , pp. 367-383
    • Ten Have, T.R.1    Kunselman, A.R.2    Pulkstenis, E.P.3    Landis, J.R.4
  • 36
    • 0034557672 scopus 로고    scopus 로고
    • The milk protein trial: Influence analysis of the dropout process
    • Thijs, H., Molenberghs, G., and Verbeke, G. (2000). The milk protein trial: Influence analysis of the dropout process. Biometrical Journal 42, 617-646.
    • (2000) Biometrical Journal , vol.42 , pp. 617-646
    • Thijs, H.1    Molenberghs, G.2    Verbeke, G.3
  • 39
    • 0024438062 scopus 로고
    • Estimation and comparison of changes in the presence of informative right censoring: Conditional linear model
    • Wu, M. C. and Bailey, K. (1989). Estimation and comparison of changes in the presence of informative right censoring: Conditional linear model. Biometrics 45, 939-955.
    • (1989) Biometrics , vol.45 , pp. 939-955
    • Wu, M.C.1    Bailey, K.2
  • 40
    • 0023921412 scopus 로고
    • Estimation and comparison of changes in the presence of informative right censoring by modeling the censoring process
    • Wu, M. C. and Carroll, R. J. (1988). Estimation and comparison of changes in the presence of informative right censoring by modeling the censoring process. Biometrics 44, 175-188.
    • (1988) Biometrics , vol.44 , pp. 175-188
    • Wu, M.C.1    Carroll, R.J.2
  • 41
    • 12244310929 scopus 로고
    • Correlated binary regression using a quadratic exponential model
    • Zhao, L. P. and Prentice, R. L. (1990). Correlated binary regression using a quadratic exponential model. Biometrika 77, 642-648.
    • (1990) Biometrika , vol.77 , pp. 642-648
    • Zhao, L.P.1    Prentice, R.L.2


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