메뉴 건너뛰기




Volumn 18, Issue 1, 2009, Pages 1-43

Missing data methods in longitudinal studies: A review

Author keywords

Expectation maximization algorithm; Incomplete data; Missing at random; Missing completely at random; Missing not at random; Pattern mixture model; Selection model; Sensitivity analyses; Shared parameter model

Indexed keywords


EID: 60749123292     PISSN: 11330686     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11749-009-0138-x     Document Type: Article
Times cited : (373)

References (104)
  • 3
    • 39849089597 scopus 로고    scopus 로고
    • A latent-class mixture model for incomplete longitudinal Gaussian data
    • C Beunckens G Molenberghs G Verbeke C Mallinckrodt 2008 A latent-class mixture model for incomplete longitudinal Gaussian data Biometrics 64 1 96 105
    • (2008) Biometrics , vol.64 , Issue.1 , pp. 96-105
    • Beunckens, C.1    Molenberghs, G.2    Verbeke, G.3    Mallinckrodt, C.4
  • 4
    • 0011241944 scopus 로고
    • Approximate inference in generalized linear mixed models
    • NE Breslow DG Clayton 1993 Approximate inference in generalized linear mixed models J Am Stat Assoc 88 9 25
    • (1993) J Am Stat Assoc , vol.88 , pp. 9-25
    • Breslow, N.E.1    Clayton, D.G.2
  • 5
    • 0037869564 scopus 로고    scopus 로고
    • A Bayesian semiparametric joint hierarchical model for longitudinal and survival data
    • ER Brown JG Ibrahim 2003 A Bayesian semiparametric joint hierarchical model for longitudinal and survival data Biometrics 59 221 228
    • (2003) Biometrics , vol.59 , pp. 221-228
    • Brown, E.R.1    Ibrahim, J.G.2
  • 6
    • 0041833567 scopus 로고    scopus 로고
    • Bayesian approaches to joint cure rate and longitudinal models with applications to cancer vaccine trials
    • ER Brown JG Ibrahim 2003 Bayesian approaches to joint cure rate and longitudinal models with applications to cancer vaccine trials Biometrics 59 686 693
    • (2003) Biometrics , vol.59 , pp. 686-693
    • Brown, E.R.1    Ibrahim, J.G.2
  • 7
    • 15044356987 scopus 로고    scopus 로고
    • A flexible b-spline model for multiple longitudinal biomarkers and survival
    • ER Brown JG Ibrahim V DeGruttola 2005 A flexible b-spline model for multiple longitudinal biomarkers and survival Biometrics 61 64 73
    • (2005) Biometrics , vol.61 , pp. 64-73
    • Brown, E.R.1    Ibrahim, J.G.2    Degruttola, V.3
  • 8
    • 0037197598 scopus 로고    scopus 로고
    • Coping with missing data in clinical trials: A model based approach applied to asthma trials
    • J Carpenter S Pocock CJ Lamm 2002 Coping with missing data in clinical trials: a model based approach applied to asthma trials Stat Med 21 1043 1066
    • (2002) Stat Med , vol.21 , pp. 1043-1066
    • Carpenter, J.1    Pocock, S.2    Lamm, C.J.3
  • 9
    • 0035102205 scopus 로고    scopus 로고
    • Maximum likelihood methods for cure rate models with missing covariates
    • M-H Chen JG Ibrahim 2002 Maximum likelihood methods for cure rate models with missing covariates Biometrics 57 43 52
    • (2002) Biometrics , vol.57 , pp. 43-52
    • Chen, M.-H.1    Ibrahim, J.G.2
  • 10
    • 0036616826 scopus 로고    scopus 로고
    • Bayesian methods for missing covariates in cure rate models
    • M-H Chen JG Ibrahim SR Lipsitz 2002 Bayesian methods for missing covariates in cure rate models Lifetime Data Anal 8 117 146
    • (2002) Lifetime Data Anal , vol.8 , pp. 117-146
    • Chen, M.-H.1    Ibrahim, J.G.2    Lipsitz, S.R.3
  • 11
    • 2942538581 scopus 로고    scopus 로고
    • Propriety of the posterior distribution and existence of the maximum likelihood estimator for regression models with covariates missing at random
    • M-H Chen JG Ibrahim Q-M Shao 2004 Propriety of the posterior distribution and existence of the maximum likelihood estimator for regression models with covariates missing at random J Am Stat Assoc 99 421 438
    • (2004) J Am Stat Assoc , vol.99 , pp. 421-438
    • Chen, M.-H.1    Ibrahim, J.G.2    Shao, Q.-M.3
  • 12
    • 3442892535 scopus 로고    scopus 로고
    • A new joint model for longitudinal and survival data with a cure fraction
    • M-H Chen JG Ibrahim D Sinha 2004 A new joint model for longitudinal and survival data with a cure fraction J Multivar Anal 91 18 34
    • (2004) J Multivar Anal , vol.91 , pp. 18-34
    • Chen, M.-H.1    Ibrahim, J.G.2    Sinha, D.3
  • 13
    • 33845764730 scopus 로고    scopus 로고
    • Posterior propriety anc computation for the Cox regression model with applications to missing covariates
    • M-H Chen JG Ibrahim Q-M Shao 2006 Posterior propriety anc computation for the Cox regression model with applications to missing covariates Biometrika 93 791 807
    • (2006) Biometrika , vol.93 , pp. 791-807
    • Chen, M.-H.1    Ibrahim, J.G.2    Shao, Q.-M.3
  • 14
    • 68949218909 scopus 로고    scopus 로고
    • Model identifiability for the Cox regression model with applications to missing covariates
    • in press
    • Chen M-H, Ibrahim JG, Shao Q-M (2009) Model identifiability for the Cox regression model with applications to missing covariates. J Multivar Anal (in press)
    • (2009) J Multivar Anal
    • Chen, M.-H.1    Ibrahim, J.G.2    Shao, Q.-M.3
  • 15
    • 33645056671 scopus 로고    scopus 로고
    • Missing covariate and response data in regression models
    • Q Chen JG Ibrahim 2006 Missing covariate and response data in regression models Biometrics 62 177 184
    • (2006) Biometrics , vol.62 , pp. 177-184
    • Chen, Q.1    Ibrahim, J.G.2
  • 16
    • 38349073376 scopus 로고    scopus 로고
    • Sieve maximum likelihood estimation for regression models with covariates missing at random
    • Q Chen D Zeng JG Ibrahim 2007 Sieve maximum likelihood estimation for regression models with covariates missing at random J Am Stat Assoc 102 1309 1317
    • (2007) J Am Stat Assoc , vol.102 , pp. 1309-1317
    • Chen, Q.1    Zeng, D.2    Ibrahim, J.G.3
  • 17
    • 43049101600 scopus 로고    scopus 로고
    • Theory and inference for regression models with missing responses and covariates
    • Q Chen JG Ibrahim M-H Chen P Senchaudhuri 2008 Theory and inference for regression models with missing responses and covariates J Multivar Anal 99 1302 1331
    • (2008) J Multivar Anal , vol.99 , pp. 1302-1331
    • Chen, Q.1    Ibrahim, J.G.2    Chen, M.-H.3    Senchaudhuri, P.4
  • 18
    • 33745288267 scopus 로고    scopus 로고
    • Joint models for multivariate longitudinal and survival data
    • Y Chi JG Ibrahim 2006 Joint models for multivariate longitudinal and survival data Biometrics 62 432 445
    • (2006) Biometrics , vol.62 , pp. 432-445
    • Chi, Y.1    Ibrahim, J.G.2
  • 19
    • 34547502683 scopus 로고    scopus 로고
    • A new class of joint models for longitudinal and survival data accomodating zero and zon-zero cure fractions: A case study of an international breast cancer study group trial
    • Y Chi JG Ibrahim 2007 A new class of joint models for longitudinal and survival data accomodating zero and zon-zero cure fractions: a case study of an international breast cancer study group trial Stat Sin 17 445 462
    • (2007) Stat Sin , vol.17 , pp. 445-462
    • Chi, Y.1    Ibrahim, J.G.2
  • 20
    • 0001490588 scopus 로고
    • Assessment of local influence
    • RD Cook 1986 Assessment of local influence J R Stat Soc Ser B 48 133 169
    • (1986) J R Stat Soc ser B , vol.48 , pp. 133-169
    • Cook, R.D.1
  • 21
    • 0002276548 scopus 로고    scopus 로고
    • Bayesian tobit modeling of longitudinal ordinal clinical trial compliance data with nonignorable missingness
    • MK Cowles BP Carlin JE Connett 1996 Bayesian tobit modeling of longitudinal ordinal clinical trial compliance data with nonignorable missingness J Am Stat Assoc 91 86 98
    • (1996) J Am Stat Assoc , vol.91 , pp. 86-98
    • Cowles, M.K.1    Carlin, B.P.2    Connett, J.E.3
  • 24
    • 0028627762 scopus 로고
    • Modelling progression of CD4 lymphocyte count and its relationship to survival time
    • V DeGruttola XM Tu 1994 Modelling progression of CD4 lymphocyte count and its relationship to survival time Biometrics 50 1003 1014
    • (1994) Biometrics , vol.50 , pp. 1003-1014
    • Degruttola, V.1    Tu, X.M.2
  • 25
    • 0002629270 scopus 로고
    • Maximum likelihood from incomplete data via the em algorithm (with discussion)
    • AP Dempster NM Laird DB Rubin 1977 Maximum likelihood from incomplete data via the EM algorithm (with discussion) J R Stat Soc Ser B 39 1 38
    • (1977) J R Stat Soc ser B , vol.39 , pp. 1-38
    • Dempster, A.P.1    Laird, N.M.2    Rubin, D.B.3
  • 26
    • 4243828610 scopus 로고
    • Informative drop-out in longitudinal data analysis (with discussion)
    • P Diggle MG Kenward 1994 Informative drop-out in longitudinal data analysis (with discussion) Appl Stat 43 49 93
    • (1994) Appl Stat , vol.43 , pp. 49-93
    • Diggle, P.1    Kenward, M.G.2
  • 28
    • 0041175330 scopus 로고    scopus 로고
    • The Muscatine children's obesity data reanalysed using pattern mixture models
    • A Ekholm C Skinner 1998 The Muscatine children's obesity data reanalysed using pattern mixture models Appl Stat 47 251 263
    • (1998) Appl Stat , vol.47 , pp. 251-263
    • Ekholm, A.1    Skinner, C.2
  • 29
    • 0029763749 scopus 로고    scopus 로고
    • Simultaneously modelling censored survival data and repeatedly measured covariates: A Gibbs sampling approach
    • CL Faucett DC Thomas 1996 Simultaneously modelling censored survival data and repeatedly measured covariates: a Gibbs sampling approach Stat Med 15 1663 1685
    • (1996) Stat Med , vol.15 , pp. 1663-1685
    • Faucett, C.L.1    Thomas, D.C.2
  • 30
    • 0001216089 scopus 로고    scopus 로고
    • Generalized linear mixture models for handling nonignorable dropouts in longitudinal studies
    • GM Fitzmaurice NM Laird 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.M.1    Laird, N.M.2
  • 31
    • 0035105253 scopus 로고    scopus 로고
    • Bias in estimating association parameters for longitudinal binary responses with drop-outs
    • GM Fitzmaurice SR Lipsitz G Molenberghs JG Ibrahim 2001 Bias in estimating association parameters for longitudinal binary responses with drop-outs Biometrics 57 15 21
    • (2001) Biometrics , vol.57 , pp. 15-21
    • Fitzmaurice, G.M.1    Lipsitz, S.R.2    Molenberghs, G.3    Ibrahim, J.G.4
  • 33
    • 33745471883 scopus 로고    scopus 로고
    • Estimation in regression models for longitudinal binary data with outcome-dependent follow-up
    • GM Fitzmaurice SR Lipsitz JG Ibrahim R Gelber S Lipshultz 2006 Estimation in regression models for longitudinal binary data with outcome-dependent follow-up Biostatistics 7 469 485
    • (2006) Biostatistics , vol.7 , pp. 469-485
    • Fitzmaurice, G.M.1    Lipsitz, S.R.2    Ibrahim, J.G.3    Gelber, R.4    Lipshultz, S.5
  • 35
    • 0029028456 scopus 로고
    • An approximate generalized linear model with random effects for informative missing data
    • D Follman M Wu 1995 An approximate generalized linear model with random effects for informative missing data Biometrics 51 151 168
    • (1995) Biometrics , vol.51 , pp. 151-168
    • Follman, D.1    Wu, M.2
  • 36
    • 63049085336 scopus 로고    scopus 로고
    • Variable selection for regression models with missing data
    • in press
    • Garcia RI, Ibrahim JG, Zhu H (2009) Variable selection for regression models with missing data. Stat Sin (in press)
    • (2009) Stat Sin
    • Garcia, R.I.1    Ibrahim, J.G.2    Zhu, H.3
  • 37
    • 0000324169 scopus 로고
    • Adaptive rejection sampling for Gibbs sampling
    • WR Gilks P Wild 1992 Adaptive rejection sampling for Gibbs sampling Appl Stat 41 337 348
    • (1992) Appl Stat , vol.41 , pp. 337-348
    • Gilks, W.R.1    Wild, P.2
  • 38
    • 0000710136 scopus 로고    scopus 로고
    • Joint modelling of longitudinal measurements and event time data
    • R Henderson P Diggle A Dobson 2000 Joint modelling of longitudinal measurements and event time data Biostatistics 1 465 480
    • (2000) Biostatistics , vol.1 , pp. 465-480
    • Henderson, R.1    Diggle, P.2    Dobson, A.3
  • 39
    • 1842715135 scopus 로고    scopus 로고
    • Likelihood-based methods for missing covariates in the Cox proportional hazards model
    • AH Herring JG Ibrahim 2001 Likelihood-based methods for missing covariates in the Cox proportional hazards model J Am Stat Assoc 96 292 302
    • (2001) J Am Stat Assoc , vol.96 , pp. 292-302
    • Herring, A.H.1    Ibrahim, J.G.2
  • 40
    • 10844238448 scopus 로고    scopus 로고
    • Maximum likelihood estimation in random effects cure rate models with nonignorably missing covariates
    • AH Herring JG Ibrahim 2002 Maximum likelihood estimation in random effects cure rate models with nonignorably missing covariates Biostatistics 3 387 405
    • (2002) Biostatistics , vol.3 , pp. 387-405
    • Herring, A.H.1    Ibrahim, J.G.2
  • 42
    • 2342659697 scopus 로고    scopus 로고
    • Nonignorably missing covariate data in survival analysis: A case study of an international breast cancer study group trial
    • AH Herring JG Ibrahim SR Lipsitz 2004 Nonignorably missing covariate data in survival analysis: a case study of an international breast cancer study group trial Appl Stat 53 293 310
    • (2004) Appl Stat , vol.53 , pp. 293-310
    • Herring, A.H.1    Ibrahim, J.G.2    Lipsitz, S.R.3
  • 43
    • 0031032359 scopus 로고    scopus 로고
    • Mixture models for the joint distribution of repeated measures and event times
    • JW Hogan NM Laird 1997 Mixture models for the joint distribution of repeated measures and event times Stat Med 16 239 257
    • (1997) Stat Med , vol.16 , pp. 239-257
    • Hogan, J.W.1    Laird, N.M.2
  • 44
    • 0031802268 scopus 로고    scopus 로고
    • Increasing efficiency from censored survival data using random effects from longitudinal covariates
    • JW Hogan NM Laird 1998 Increasing efficiency from censored survival data using random effects from longitudinal covariates Stat Methods Med Res 7 28 48
    • (1998) Stat Methods Med Res , vol.7 , pp. 28-48
    • Hogan, J.W.1    Laird, N.M.2
  • 45
    • 14944383985 scopus 로고    scopus 로고
    • Bayesian analysis for generalized linear models with nonignorably missing covariates
    • L Huang M-H Chen JG Ibrahim 2005 Bayesian analysis for generalized linear models with nonignorably missing covariates Biometrics 61 767 780
    • (2005) Biometrics , vol.61 , pp. 767-780
    • Huang, L.1    Chen, M.-H.2    Ibrahim, J.G.3
  • 46
    • 84950431939 scopus 로고
    • Incomplete data in generalized linear models
    • JG Ibrahim 1990 Incomplete data in generalized linear models J Am Stat Assoc 85 765 769
    • (1990) J Am Stat Assoc , vol.85 , pp. 765-769
    • Ibrahim, J.G.1
  • 47
    • 0033474233 scopus 로고    scopus 로고
    • Missing covariates in generalized linear models when the missing data mechanism is nonignorable
    • JG Ibrahim SR Lipsitz M-H Chen 1999 Missing covariates in generalized linear models when the missing data mechanism is nonignorable J R Stat Soc Ser B 61 173 190
    • (1999) J R Stat Soc ser B , vol.61 , pp. 173-190
    • Ibrahim, J.G.1    Lipsitz, S.R.2    Chen, M.-H.3
  • 48
    • 0032969451 scopus 로고    scopus 로고
    • Monte Carlo em for missing covariates in parametric regression models
    • JG Ibrahim MH Chen SR Lipsitz 1999 Monte Carlo EM for missing covariates in parametric regression models Biometrics 55 591 596
    • (1999) Biometrics , vol.55 , pp. 591-596
    • Ibrahim, J.G.1    Chen, M.H.2    Lipsitz, S.R.3
  • 49
    • 0037507563 scopus 로고    scopus 로고
    • Missing responses in generalized linear mixed models when the missing data mechanism is nonignorable
    • JG Ibrahim M-H Chen SR Lipsitz 2001 Missing responses in generalized linear mixed models when the missing data mechanism is nonignorable Biometrika 88 551 564
    • (2001) Biometrika , vol.88 , pp. 551-564
    • Ibrahim, J.G.1    Chen, M.-H.2    Lipsitz, S.R.3
  • 50
    • 0036016749 scopus 로고    scopus 로고
    • Bayesian methods for generalized linear models with covariates missing at random
    • JG Ibrahim M-H Chen SR Lipsitz 2002 Bayesian methods for generalized linear models with covariates missing at random Can J Stat 30 55 78
    • (2002) Can J Stat , vol.30 , pp. 55-78
    • Ibrahim, J.G.1    Chen, M.-H.2    Lipsitz, S.R.3
  • 51
    • 3442883055 scopus 로고    scopus 로고
    • Bayesian methods for joint modeling of longitudinal and survival data with applicants to cancer vaccine trials
    • JG Ibrahim M-H Chen D Sinha 2004 Bayesian methods for joint modeling of longitudinal and survival data with applicants to cancer vaccine trials Stat Sin 14 863 883
    • (2004) Stat Sin , vol.14 , pp. 863-883
    • Ibrahim, J.G.1    Chen, M.-H.2    Sinha, D.3
  • 52
    • 14944360441 scopus 로고    scopus 로고
    • Missing data methods in generalized linear models: A comparative review
    • JG Ibrahim M-H Chen SR Lipsitz AH Herring 2005 Missing data methods in generalized linear models: a comparative review J Am Stat Assoc 100 332 346
    • (2005) J Am Stat Assoc , vol.100 , pp. 332-346
    • Ibrahim, J.G.1    Chen, M.-H.2    Lipsitz, S.R.3    Herring, A.H.4
  • 53
    • 55949129314 scopus 로고    scopus 로고
    • Bayesian variable selection for the Cox regression model with missing covariates
    • JG Ibrahim M-H Chen S Kim 2008 Bayesian variable selection for the Cox regression model with missing covariates Lifetime Data Anal 14 496 520
    • (2008) Lifetime Data Anal , vol.14 , pp. 496-520
    • Ibrahim, J.G.1    Chen, M.-H.2    Kim, S.3
  • 54
    • 63049130850 scopus 로고    scopus 로고
    • Model selection criteria for missing data problems using the em algorithm
    • JG Ibrahim H Zhu N Tang 2008 Model selection criteria for missing data problems using the EM algorithm J Am Stat Assoc 103 1648 1658
    • (2008) J Am Stat Assoc , vol.103 , pp. 1648-1658
    • Ibrahim, J.G.1    Zhu, H.2    Tang, N.3
  • 55
    • 0022966316 scopus 로고
    • Unbalanced repeated-measures models with structured covariance matrices
    • RI Jennrich MD Schluchter 1986 Unbalanced repeated-measures models with structured covariance matrices Biometrics 42 805 820
    • (1986) Biometrics , vol.42 , pp. 805-820
    • Jennrich, R.I.1    Schluchter, M.D.2
  • 56
    • 0020333131 scopus 로고
    • Random-effects models for longitudinal data
    • NM Laird JH Ware 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
  • 57
    • 0029954122 scopus 로고    scopus 로고
    • Models for empirical Bayes estimators of longitudinal CD4 counts
    • MP Lavalley V DeGruttola 1996 Models for empirical Bayes estimators of longitudinal CD4 counts Stat Med 15 2289 2305
    • (1996) Stat Med , vol.15 , pp. 2289-2305
    • Lavalley, M.P.1    Degruttola, V.2
  • 58
    • 0031744665 scopus 로고    scopus 로고
    • Local influence in linear mixed models
    • E Lesaffre G Verbeke 1998 Local influence in linear mixed models Biometrics 54 570 582
    • (1998) Biometrics , vol.54 , pp. 570-582
    • Lesaffre, E.1    Verbeke, G.2
  • 59
    • 77649173768 scopus 로고
    • Longitudinal data analysis using generalized linear models
    • K-Y Liang SL Zeger 1986 Longitudinal data analysis using generalized linear models Biometrika 73 13 22
    • (1986) Biometrika , vol.73 , pp. 13-22
    • Liang, K.-Y.1    Zeger, S.L.2
  • 60
    • 0032907299 scopus 로고    scopus 로고
    • Likelihood methods for incomplete longitudinal binary responses with incomplete categorical covariates
    • SR Lipsitz JG Ibrahim GM Fitzmaurice 1999 Likelihood methods for incomplete longitudinal binary responses with incomplete categorical covariates Biometrics 55 214 223
    • (1999) Biometrics , vol.55 , pp. 214-223
    • Lipsitz, S.R.1    Ibrahim, J.G.2    Fitzmaurice, G.M.3
  • 61
    • 0442278074 scopus 로고    scopus 로고
    • A new weighted estimating equation for missing covariate data with properties similar to maximum likelihood
    • SR Lipsitz JG Ibrahim LP Zhao 1999 A new weighted estimating equation for missing covariate data with properties similar to maximum likelihood J Am Stat Assoc 94 1147 1160
    • (1999) J Am Stat Assoc , vol.94 , pp. 1147-1160
    • Lipsitz, S.R.1    Ibrahim, J.G.2    Zhao, L.P.3
  • 62
    • 0034360865 scopus 로고    scopus 로고
    • Using a Box-Cox transformation in the analysis of longitudinal data with incomplete responses
    • SR Lipsitz JG Ibrahim G Molenberghs 2000 Using a Box-Cox transformation in the analysis of longitudinal data with incomplete responses Appl Stat 49 287 296
    • (2000) Appl Stat , vol.49 , pp. 287-296
    • Lipsitz, S.R.1    Ibrahim, J.G.2    Molenberghs, G.3
  • 65
    • 21144483152 scopus 로고
    • Pattern-mixture models for multivariate incomplete data
    • RJA Little 1993 Pattern-mixture models for multivariate incomplete data J Am Stat Assoc 88 125 134
    • (1993) J Am Stat Assoc , vol.88 , pp. 125-134
    • Little, R.J.A.1
  • 66
    • 77956890002 scopus 로고
    • A class of pattern-mixture models for normal incomplete data
    • RJA Little 1994 A class of pattern-mixture models for normal incomplete data Biometrika 81 471 483
    • (1994) Biometrika , vol.81 , pp. 471-483
    • Little, R.J.A.1
  • 67
    • 84950452119 scopus 로고
    • Modeling the drop-out mechanism in repeated-measures studies
    • RJA Little 1995 Modeling the drop-out mechanism in repeated-measures studies J Am Stat Assoc 90 1113 1121
    • (1995) J Am Stat Assoc , vol.90 , pp. 1113-1121
    • Little, R.J.A.1
  • 68
    • 0029995115 scopus 로고    scopus 로고
    • Pattern-mixture models for multivariate incomplete data with covariates
    • RJA Little Y Wang 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
  • 70
    • 0001044972 scopus 로고
    • Finding the observed information matrix when using the em algorithm
    • T Louis 1982 Finding the observed information matrix when using the EM algorithm J R Stat Soc Ser B 44 226 233
    • (1982) J R Stat Soc ser B , vol.44 , pp. 226-233
    • Louis, T.1
  • 71
    • 0001232538 scopus 로고
    • A fast improvement to the em algorithm on its own terms
    • I Meilijson 1989 A fast improvement to the EM algorithm on its own terms J R Stat Soc Ser B 51 127 138
    • (1989) J R Stat Soc ser B , vol.51 , pp. 127-138
    • Meilijson, I.1
  • 74
    • 0001986642 scopus 로고    scopus 로고
    • The analysis of longitudinal ordinal data with nonrandom drop-out
    • G Molenberghs MG Kenward E Lesaffre 1997 The analysis of longitudinal ordinal data with nonrandom drop-out Biometrika 84 33 4
    • (1997) Biometrika , vol.84 , pp. 33-4
    • Molenberghs, G.1    Kenward, M.G.2    Lesaffre, E.3
  • 75
    • 21144479140 scopus 로고
    • Modeling disease marker processes in AIDS
    • Y Pawitan S Self 1993 Modeling disease marker processes in AIDS J Am Stat Assoc 88 719 726
    • (1993) J Am Stat Assoc , vol.88 , pp. 719-726
    • Pawitan, Y.1    Self, S.2
  • 76
    • 0024520844 scopus 로고
    • Surrogate endpoints in clinical trials: Definitions and operational criteria
    • RL Prentice 1989 Surrogate endpoints in clinical trials: definitions and operational criteria Stat Med 8 431 440
    • (1989) Stat Med , vol.8 , pp. 431-440
    • Prentice, R.L.1
  • 77
    • 0036921290 scopus 로고    scopus 로고
    • Validation of surrogate endpoints in multiple randomized clinical trials with discrete outcomes
    • D Renard H Geys G Molenberghs T Burzykowski M Buyse 2002 Validation of surrogate endpoints in multiple randomized clinical trials with discrete outcomes Biom J 44 921 935
    • (2002) Biom J , vol.44 , pp. 921-935
    • Renard, D.1    Geys, H.2    Molenberghs, G.3    Burzykowski, T.4    Buyse, M.5
  • 78
    • 40249113335 scopus 로고    scopus 로고
    • Shared parameter models under random-effects misspecification
    • D Rizopoulos G Verbeke G Molenberghs 2008 Shared parameter models under random-effects misspecification Biometrika 94 63 74
    • (2008) Biometrika , vol.94 , pp. 63-74
    • Rizopoulos, D.1    Verbeke, G.2    Molenberghs, G.3
  • 79
    • 84950421496 scopus 로고
    • Analysis of semiparametric regression models for repeated outcomes in the presence of missing data
    • JM Robins A Rotnitzky LP Zhao 1995 Analysis of semiparametric regression models for repeated outcomes in the presence of missing data J Am Stat Assoc 90 429 106 121
    • (1995) J Am Stat Assoc , vol.90 , Issue.429 , pp. 106-121
    • Robins, J.M.1    Rotnitzky, A.2    Zhao, L.P.3
  • 80
    • 0032264836 scopus 로고    scopus 로고
    • Semiparametric regression for repeated outcomes with nonignorable nonresponse
    • A Rotnitzky JM Robins DO Scharfstein 1998 Semiparametric regression for repeated outcomes with nonignorable nonresponse J Am Stat Assoc 93 1321 1339
    • (1998) J Am Stat Assoc , vol.93 , pp. 1321-1339
    • Rotnitzky, A.1    Robins, J.M.2    Scharfstein, D.O.3
  • 81
    • 0017133178 scopus 로고
    • Inference and missing data
    • DB Rubin 1976 Inference and missing data Biometrika 63 3 581 592
    • (1976) Biometrika , vol.63 , Issue.3 , pp. 581-592
    • Rubin, D.B.1
  • 83
    • 0442278084 scopus 로고    scopus 로고
    • Adjusting for nonignorable drop-out using semiparametric nonresponse models
    • DO Scharfstein A Rotnitzky JM Robins 1999 Adjusting for nonignorable drop-out using semiparametric nonresponse models J Am Stat Assoc 94 1096 1120
    • (1999) J Am Stat Assoc , vol.94 , pp. 1096-1120
    • Scharfstein, D.O.1    Rotnitzky, A.2    Robins, J.M.3
  • 84
    • 0027092589 scopus 로고
    • Methods for the analysis of informatively censored longitudinal data
    • MD Schluchter 1992 Methods for the analysis of informatively censored longitudinal data Stat Med 11 1861 1870
    • (1992) Stat Med , vol.11 , pp. 1861-1870
    • Schluchter, M.D.1
  • 85
    • 63049126161 scopus 로고    scopus 로고
    • Local influence for generalized linear models with missing covariates
    • in press
    • Shi X, Zhu H, Ibrahim JG (2009) Local influence for generalized linear models with missing covariates. Biometrics (in press)
    • (2009) Biometrics
    • Shi, X.1    Zhu, H.2    Ibrahim, J.G.3
  • 86
    • 0346102882 scopus 로고    scopus 로고
    • Maximum likelihood methods for nonignorable responses and covariates in random effects models
    • AL Stubbendick JG Ibrahim 2003 Maximum likelihood methods for nonignorable responses and covariates in random effects models Biometrics 59 1140 1150
    • (2003) Biometrics , vol.59 , pp. 1140-1150
    • Stubbendick, A.L.1    Ibrahim, J.G.2
  • 87
    • 33846492873 scopus 로고    scopus 로고
    • Likelihood-based inference with nonignorably missing responses and covariates in models for discrete longitudinal data
    • AL Stubbendick JG Ibrahim 2006 Likelihood-based inference with nonignorably missing responses and covariates in models for discrete longitudinal data Stat Sin 16 1143 1167
    • (2006) Stat Sin , vol.16 , pp. 1143-1167
    • Stubbendick, A.L.1    Ibrahim, J.G.2
  • 88
    • 21844510172 scopus 로고
    • A stochastic model for analysis of longitudinal AIDS data
    • JMG Taylor WG Cumberland JP Sy 1994 A stochastic model for analysis of longitudinal AIDS data J Am Stat Assoc 89 727 736
    • (1994) J Am Stat Assoc , vol.89 , pp. 727-736
    • Taylor, J.M.G.1    Cumberland, W.G.2    Sy, J.P.3
  • 90
    • 0039982650 scopus 로고    scopus 로고
    • Analysis of longitudinal data with nonignorable nonmonotone missing values
    • AB Troxel DP Harrington SR Lipsitz 1998 Analysis of longitudinal data with nonignorable nonmonotone missing values Appl Stat 47 425 438
    • (1998) Appl Stat , vol.47 , pp. 425-438
    • Troxel, A.B.1    Harrington, D.P.2    Lipsitz, S.R.3
  • 91
    • 0005215991 scopus 로고    scopus 로고
    • Marginal models for the analysis of longitudinal measurements with nonignorable non-monotone missing data
    • AB Troxel SR Lipsitz DP Harrington 1998 Marginal models for the analysis of longitudinal measurements with nonignorable non-monotone missing data Biometrika 85 661 672
    • (1998) Biometrika , vol.85 , pp. 661-672
    • Troxel, A.B.1    Lipsitz, S.R.2    Harrington, D.P.3
  • 92
    • 21844506206 scopus 로고
    • Modeling the relationship of survival to longitudinal data measured with error. Applications to survival and CD4 counts in patients with AIDS
    • AA Tsiatis V DeGruttola MS Wulfsohn 1995 Modeling the relationship of survival to longitudinal data measured with error. Applications to survival and CD4 counts in patients with AIDS J Am Stat Assoc 90 27 37
    • (1995) J Am Stat Assoc , vol.90 , pp. 27-37
    • Tsiatis, A.A.1    Degruttola, V.2    Wulfsohn, M.S.3
  • 94
    • 0016335739 scopus 로고
    • Quasi-likelihood methods, generalised linear models, and the Gauss-Newton method
    • RWM Wedderburn 1974 Quasi-likelihood methods, generalised linear models, and the Gauss-Newton method Biometrika 61 439 447
    • (1974) Biometrika , vol.61 , pp. 439-447
    • Wedderburn, R.W.M.1
  • 95
    • 84950432017 scopus 로고
    • A Monte Carlo implementation of the em algorithm and the poor man's data augmentation algorithms
    • GC Wei MA Tanner 1990 A Monte Carlo implementation of the EM algorithm and the poor man's data augmentation algorithms J Am Stat Assoc 85 699 704
    • (1990) J Am Stat Assoc , vol.85 , pp. 699-704
    • Wei, G.C.1    Tanner, M.A.2
  • 96
    • 84949346776 scopus 로고
    • Generalized linear models: A pseudo-likelihood approach
    • R Wolfinger M O'Connell 1993 Generalized linear models: a pseudo-likelihood approach J Stat Comput Simul 48 233 243
    • (1993) J Stat Comput Simul , vol.48 , pp. 233-243
    • Wolfinger, R.1    O'Connell, M.2
  • 97
    • 0001206524 scopus 로고
    • Analysis of categorical incomplete longitudinal data
    • RF Woolson WR Clarke 1984 Analysis of categorical incomplete longitudinal data J R Stat Soc Ser A 147 87 99
    • (1984) J R Stat Soc ser A , vol.147 , pp. 87-99
    • Woolson, R.F.1    Clarke, W.R.2
  • 98
    • 0023779040 scopus 로고
    • Analysing changes in the presence of informative right censoring caused by death and withdrawal
    • MC Wu KR Bailey 1988 Analysing changes in the presence of informative right censoring caused by death and withdrawal Stat Med 7 337 346
    • (1988) Stat Med , vol.7 , pp. 337-346
    • Wu, M.C.1    Bailey, K.R.2
  • 99
    • 0023921412 scopus 로고
    • Estimation and comparison of changes in the presence of informative right censoring by modeling the censoring process
    • MC Wu RJ Carroll 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
  • 100
    • 0024438062 scopus 로고
    • Estimation and comparison of changes in the presence of informative right censoring: Conditional linear model
    • MC Wu KR Bailey 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.R.2
  • 101
    • 0035650134 scopus 로고    scopus 로고
    • Joint analysis of longitudinal data comprising repeated measures and times to events
    • J Xu SL Zeger 2001 Joint analysis of longitudinal data comprising repeated measures and times to events Appl Stat 50 375 387
    • (2001) Appl Stat , vol.50 , pp. 375-387
    • Xu, J.1    Zeger, S.L.2
  • 102
    • 0022673130 scopus 로고
    • Longitudinal data analysis for discrete and continuous outcomes
    • SL Zeger K-Y Liang 1986 Longitudinal data analysis for discrete and continuous outcomes Biometrics 42 121 130
    • (1986) Biometrics , vol.42 , pp. 121-130
    • Zeger, S.L.1    Liang, K.-Y.2
  • 103
    • 0035648116 scopus 로고    scopus 로고
    • Local influence for incomplete-data models
    • H-T Zhu S-Y Lee 2001 Local influence for incomplete-data models J R Stat Soc Ser B 63 111 126
    • (2001) J R Stat Soc ser B , vol.63 , pp. 111-126
    • Zhu, H.-T.1    Lee, S.-Y.2
  • 104
    • 63049116080 scopus 로고    scopus 로고
    • Diagnostic measures for generalized linear models with missing covariates
    • in press
    • Zhu H, Ibrahim JG, Shi X (2009) Diagnostic measures for generalized linear models with missing covariates. Scand J Stat (in press)
    • (2009) Scand J Stat
    • Zhu, H.1    Ibrahim, J.G.2    Shi, X.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.