메뉴 건너뛰기




Volumn 23, Issue 2, 2008, Pages 201-218

Formal and informal model selection with incomplete data

Author keywords

Interval of ignorance; Linear mixed model; Missing at random; Missing not at random; Multivariate normal; Sensitivity analysis

Indexed keywords


EID: 50849094901     PISSN: 08834237     EISSN: None     Source Type: Journal    
DOI: 10.1214/07-STS253     Document Type: Article
Times cited : (16)

References (85)
  • 1
    • 0000828942 scopus 로고
    • Missing observations in multivariate statistics. I. Review of the literature
    • MR0203865
    • AFIFI, A. and ELASHOFF, R. (1966). Missing observations in multivariate statistics. I. Review of the literature. J. Amer. Statist. Assoc. 61 595-604. MR0203865
    • (1966) J. Amer. Statist. Assoc , vol.61 , pp. 595-604
    • AFIFI, A.1    ELASHOFF, R.2
  • 2
    • 50849102480 scopus 로고    scopus 로고
    • AGRESTI, A. (2002). Categorical Data Analysis, 2nd ed. Wiley, New York. MR1914507
    • AGRESTI, A. (2002). Categorical Data Analysis, 2nd ed. Wiley, New York. MR1914507
  • 3
    • 84936025682 scopus 로고
    • Estimation of linear models with incomplete data
    • ALLISON, P. D. (1987). Estimation of linear models with incomplete data. Sociology Methodology 17 71-103.
    • (1987) Sociology Methodology , vol.17 , pp. 71-103
    • ALLISON, P.D.1
  • 4
    • 0346880128 scopus 로고    scopus 로고
    • Identification of causal effects using instrumental variables
    • ANGRIST, J. D., IMBENS, G. W. and RUBIN, D. B. (1996). Identification of causal effects using instrumental variables. J. Amer. Statist. Assoc. 91 444-455.
    • (1996) J. Amer. Statist. Assoc , vol.91 , pp. 444-455
    • ANGRIST, J.D.1    IMBENS, G.W.2    RUBIN, D.B.3
  • 5
    • 0026550210 scopus 로고
    • Closed-form estimates for missing counts in two-way contingency tables
    • BAKER, S. G., ROSENBERGER, W. F. and DERSIMONIAN, R. (1992). Closed-form estimates for missing counts in two-way contingency tables. Statistics in Medicine 11 643-657.
    • (1992) Statistics in Medicine , vol.11 , pp. 643-657
    • BAKER, S.G.1    ROSENBERGER, W.F.2    DERSIMONIAN, R.3
  • 6
    • 0023453271 scopus 로고
    • Diagnostics for mixed-model analysis of variance
    • MR0918527
    • BECKMAN, R. J., NACHTSHEIM, C. J. and COOK, R. D. (1987). Diagnostics for mixed-model analysis of variance. Technometrics 29 413-426. MR0918527
    • (1987) Technometrics , vol.29 , pp. 413-426
    • BECKMAN, R.J.1    NACHTSHEIM, C.J.2    COOK, R.D.3
  • 7
    • 50849103179 scopus 로고    scopus 로고
    • BEUNCKENS, C., MOLENBERGHS, G., VERBEKE, G. and MALLINCKRODT, C. (2007). A latent-classs mixture model for incomplete longitudinal Gaussian data. Biometrics 63 000-000.
    • BEUNCKENS, C., MOLENBERGHS, G., VERBEKE, G. and MALLINCKRODT, C. (2007). A latent-classs mixture model for incomplete longitudinal Gaussian data. Biometrics 63 000-000.
  • 8
    • 50849084668 scopus 로고    scopus 로고
    • CHATTERJEE, S. and HADI, A. S. (1988). Sensitivity Analysis in Linear Regression. Wiley, New York. MR0939610
    • CHATTERJEE, S. and HADI, A. S. (1988). Sensitivity Analysis in Linear Regression. Wiley, New York. MR0939610
  • 10
    • 0002627582 scopus 로고    scopus 로고
    • Inference from non-random samples (with discussion)
    • MR1436555
    • COPAS, J. B. and LI, H. G. (1997). Inference from non-random samples (with discussion). J. Roy. Statist. Soc. Ser. B 59 55-96. MR1436555
    • (1997) J. Roy. Statist. Soc. Ser. B , vol.59 , pp. 55-96
    • COPAS, J.B.1    LI, H.G.2
  • 11
    • 50849108030 scopus 로고    scopus 로고
    • D'AGOSTINO, R. B. and STEPHENS, M. A. (1986). Goodness-of-Fit Techniques. Dekker, New York. MR0874534
    • D'AGOSTINO, R. B. and STEPHENS, M. A. (1986). Goodness-of-Fit Techniques. Dekker, New York. MR0874534
  • 12
    • 0002629270 scopus 로고
    • Maximum likelihood from incomplete data via the EMalgorithm (with discussion)
    • MR0501537
    • DEMPSTER, A. P., LAIRD, N. M. and RUBIN, D. B. (1977). Maximum likelihood from incomplete data via the EMalgorithm (with discussion). J. Roy. Statist. Soc. Ser. B 39 1-38. MR0501537
    • (1977) J. Roy. Statist. Soc. Ser. B , vol.39 , pp. 1-38
    • DEMPSTER, A.P.1    LAIRD, N.M.2    RUBIN, D.B.3
  • 13
    • 0024887538 scopus 로고
    • Testing for random dropouts in repeated measurement data
    • DIGGLE, P. J. (1989). Testing for random dropouts in repeated measurement data. Biometrics 45 1255-1258.
    • (1989) Biometrics , vol.45 , pp. 1255-1258
    • DIGGLE, P.J.1
  • 14
    • 4243828610 scopus 로고
    • Informative drop-out in longitudinal data analysis (with discussion)
    • DIGGLE, P. J. and KENWARD, M. G. (1994). Informative drop-out in longitudinal data analysis (with discussion). Appl. Statist. 43 49-93.
    • (1994) Appl. Statist , vol.43 , pp. 49-93
    • DIGGLE, P.J.1    KENWARD, M.G.2
  • 15
    • 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. Appl. Statist. 47 251-263.
    • (1998) Appl. Statist , vol.47 , pp. 251-263
    • EKHOLM, A.1    SKINNER, C.2
  • 16
    • 0000369209 scopus 로고
    • Regression models for longitudinal binary responses with informative dropouts
    • MR1354075
    • FITZMAURICE, G. M., MOLENBERGHS, G. and LIPSITZ, S. R. (1995). Regression models for longitudinal binary responses with informative dropouts. J. Roy. Statist. Soc. Ser. B 57 691-704. MR1354075
    • (1995) J. Roy. Statist. Soc. Ser. B , vol.57 , pp. 691-704
    • FITZMAURICE, G.M.1    MOLENBERGHS, G.2    LIPSITZ, S.R.3
  • 17
    • 0036188782 scopus 로고    scopus 로고
    • Principal stratification in causal inference
    • MR1891039
    • FRANGAKIS, C. E. and RUBIN, D. B. (2002). Principal stratification in causal inference. Biometrics 58 21-29. MR1891039
    • (2002) Biometrics , vol.58 , pp. 21-29
    • FRANGAKIS, C.E.1    RUBIN, D.B.2
  • 18
    • 15044358532 scopus 로고    scopus 로고
    • Multiple imputation for model checking: Completed-data plots with missing and latent data
    • MR2135847
    • GELMAN, A., VAN MECHELEN, I., VERBEKE, G., HEITJAN, D. F. and MEULDERS, M. (2005). Multiple imputation for model checking: Completed-data plots with missing and latent data. Biometrics 61 74-85. MR2135847
    • (2005) Biometrics , vol.61 , pp. 74-85
    • GELMAN, A.1    VAN MECHELEN, I.2    VERBEKE, G.3    HEITJAN, D.F.4    MEULDERS, M.5
  • 19
    • 0000996385 scopus 로고
    • The analysis of incomplete data
    • HARTLEY, H. O. and HOCKING, R. (1971). The analysis of incomplete data. Biometrics 27 7783-7808.
    • (1971) Biometrics , vol.27 , pp. 7783-7808
    • HARTLEY, H.O.1    HOCKING, R.2
  • 20
    • 50849136690 scopus 로고    scopus 로고
    • HAUG, E. J., CHOI, K. K. and KOMKOV, V. (1986). Design of Sensitivity Analysis of Structural Systems. Academic Press, Orlando, FL. MR0860040
    • HAUG, E. J., CHOI, K. K. and KOMKOV, V. (1986). Design of Sensitivity Analysis of Structural Systems. Academic Press, Orlando, FL. MR0860040
  • 21
    • 0002105479 scopus 로고    scopus 로고
    • Application of random-effects pattern-mixture models for missing data in longitudinal studies
    • HEDEKER, D. and GIBBONS, R. D. (1997). Application of random-effects pattern-mixture models for missing data in longitudinal studies. Psychological Methods 2 64-78.
    • (1997) Psychological Methods , vol.2 , pp. 64-78
    • HEDEKER, D.1    GIBBONS, R.D.2
  • 22
    • 0031032359 scopus 로고    scopus 로고
    • Mixture models for the joint distribution of repeated measures and event times
    • HOGAN, J. W. 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.W.1    LAIRD, N.M.2
  • 23
    • 84920420698 scopus 로고
    • Statistics and causal inference
    • MR0867618
    • HOLLAND, P. W. (1986). Statistics and causal inference. J. Amer. Statist. Assoc. 81 945-960. MR0867618
    • (1986) J. Amer. Statist. Assoc , vol.81 , pp. 945-960
    • HOLLAND, P.W.1
  • 27
    • 0038207121 scopus 로고    scopus 로고
    • A Local influence approach applied to binary data from a psychiatric study
    • MR1987408
    • JANSEN, I., MOLENBERGHS, G., AERTS, M., THIJS, H. and VAN TEEN, K. (2003). A Local influence approach applied to binary data from a psychiatric study. Biometrics 59 410-419. MR1987408
    • (2003) Biometrics , vol.59 , pp. 410-419
    • JANSEN, I.1    MOLENBERGHS, G.2    AERTS, M.3    THIJS, H.4    VAN5    TEEN, K.6
  • 28
    • 0022966316 scopus 로고
    • Unbalanced repeated measures models with structured covariance matrices
    • MR0872961
    • JENNRICH, R. I. and SCHLUCHTER, M. D. (1986). Unbalanced repeated measures models with structured covariance matrices. Biometrics 42 805-820. MR0872961
    • (1986) Biometrics , vol.42 , pp. 805-820
    • JENNRICH, R.I.1    SCHLUCHTER, M.D.2
  • 29
    • 0032534724 scopus 로고    scopus 로고
    • Selection models for repeated measurements with nonrandom dropout: An illustration of sensitivity
    • KENWARD, M. G. (1998). Selection models for repeated measurements with nonrandom dropout: an illustration of sensitivity. Statistics in Medicine 17 2723-2732.
    • (1998) Statistics in Medicine , vol.17 , pp. 2723-2732
    • KENWARD, M.G.1
  • 31
    • 0345734935 scopus 로고    scopus 로고
    • Likelihood based frequentist inference when data are missing at random
    • MR1665713
    • KENWARD, M. G. and MOLENBERGHS, G. (1998). Likelihood based frequentist inference when data are missing at random. Statist. Sci. 12 236-247. MR1665713
    • (1998) Statist. Sci , vol.12 , pp. 236-247
    • KENWARD, M.G.1    MOLENBERGHS, G.2
  • 32
    • 1542341537 scopus 로고    scopus 로고
    • Pattern-mixture models with proper time dependence
    • MR1966550
    • KENWARD, M.G., MOLENBERGHS, G. and THIJS, H. (2003). Pattern-mixture models with proper time dependence. Biometrika 90 53-71. MR1966550
    • (2003) Biometrika , vol.90 , pp. 53-71
    • KENWARD, M.G.1    MOLENBERGHS, G.2    THIJS, H.3
  • 33
    • 50849118639 scopus 로고    scopus 로고
    • LAIRD, N. M. (1994). Discussion of Informative dropout in longitudinal data analysis, by P. J. Diggle and M. G. Kenward. Appl. Statist. 43 84.
    • LAIRD, N. M. (1994). Discussion of "Informative dropout in longitudinal data analysis," by P. J. Diggle and M. G. Kenward. Appl. Statist. 43 84.
  • 34
    • 0031744665 scopus 로고    scopus 로고
    • Local influence in linear mixed models
    • LESAFFRE, E. and VERBEKE, G. (1998). Local influence in linear mixed models. Biometrics 54 570-582.
    • (1998) Biometrics , vol.54 , pp. 570-582
    • LESAFFRE, E.1    VERBEKE, G.2
  • 35
    • 21144483152 scopus 로고
    • Pattern-mixture models for multivariate incomplete data
    • LITTLE, R. J. A. (1993). Pattern-mixture models for multivariate incomplete data. J. Amer. Statist. Assoc. 88 125-134.
    • (1993) J. Amer. Statist. Assoc , vol.88 , pp. 125-134
    • LITTLE, R.J.A.1
  • 36
    • 77956890002 scopus 로고
    • A class of pattern-mixture models for normal incomplete data
    • MR1311091
    • LITTLE, R. J. A. (1994a). A class of pattern-mixture models for normal incomplete data. Biometrika 81 471-483. MR1311091
    • (1994) Biometrika , vol.81 , pp. 471-483
    • LITTLE, R.J.A.1
  • 37
    • 50849088501 scopus 로고    scopus 로고
    • LITTLE, R. J. A. (1994b). Discussion of Informative dropout in longitudinal data analysis, by P. J. Diggle and M. G. Kenward. Appl. Statist. 43 78.
    • LITTLE, R. J. A. (1994b). Discussion of "Informative dropout in longitudinal data analysis," by P. J. Diggle and M. G. Kenward. Appl. Statist. 43 78.
  • 38
    • 85101444608 scopus 로고    scopus 로고
    • LITTLE, R. J. A. and RUBIN, D. B. (2002). Statistical Analysis with Missing Data, 2nd ed. Wiley, New York. MR1925014
    • LITTLE, R. J. A. and RUBIN, D. B. (2002). Statistical Analysis with Missing Data, 2nd ed. Wiley, New York. MR1925014
  • 39
    • 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
  • 40
    • 0030460385 scopus 로고    scopus 로고
    • Intent-to-treat analysis for longitudinal studies with drop-outs
    • LITTLE, R. J. A. and YAU, L. (1996). Intent-to-treat analysis for longitudinal studies with drop-outs. Biometrics 52 1324-1333.
    • (1996) Biometrics , vol.52 , pp. 1324-1333
    • LITTLE, R.J.A.1    YAU, L.2
  • 41
    • 0026497615 scopus 로고
    • Modeling incomplete longitudinal and cross-sectional data using latent growth structural models
    • MCARDLE, J. J. and HAMAGANI, F. (1992). Modeling incomplete longitudinal and cross-sectional data using latent growth structural models. Experimental Aging Research 18 145-166.
    • (1992) Experimental Aging Research , vol.18 , pp. 145-166
    • MCARDLE, J.J.1    HAMAGANI, F.2
  • 43
    • 0037273401 scopus 로고    scopus 로고
    • Assessing response profiles from incomplete longitudinal clinical trial data with subject dropout under regulatory conditions
    • MALLINCKRODT, C. H., SCOTT CLARK, W., CARROLL, R. J. and MOLENBERGHS, G. (2003b). Assessing response profiles from incomplete longitudinal clinical trial data with subject dropout under regulatory conditions. J. Biopharmaceutical Statistics 13 179-190.
    • (2003) J. Biopharmaceutical Statistics , vol.13 , pp. 179-190
    • MALLINCKRODT, C.H.1    SCOTT CLARK, W.2    CARROLL, R.J.3    MOLENBERGHS, G.4
  • 44
    • 0037197628 scopus 로고    scopus 로고
    • Selection models and pattern-mixture models to analyze longitudinal quality of life data subject to dropout
    • MICHIELS, B., MOLENBERGHS, G., BIJNENS, L. and VANGENEUGDEN, T. (2002). Selection models and pattern-mixture models to analyze longitudinal quality of life data subject to dropout. Statistics in Medicine 21 1023-1041.
    • (2002) Statistics in Medicine , vol.21 , pp. 1023-1041
    • MICHIELS, B.1    MOLENBERGHS, G.2    BIJNENS, L.3    VANGENEUGDEN, T.4
  • 45
    • 0032885858 scopus 로고    scopus 로고
    • Selection models and pattern-mixture models for incomplete categorical data with covariates
    • MICHIELS, B., MOLENBERGHS, G. and LIPSITZ, S. R. (1999). Selection models and pattern-mixture models for incomplete categorical data with covariates. Biometrics 55 978-983.
    • (1999) Biometrics , vol.55 , pp. 978-983
    • MICHIELS, B.1    MOLENBERGHS, G.2    LIPSITZ, S.R.3
  • 46
    • 38949124382 scopus 로고    scopus 로고
    • Every missingness not at random model has a missingness at random counterpart with equal fit
    • MOLENBERGHS, G., BEUNCKENS, C., SOTTO, C. and KEN-WARD, M. G. (2007). Every missingness not at random model has a missingness at random counterpart with equal fit. J. Roy. Statist. Soc. Ser. B 70 371-388.
    • (2007) J. Roy. Statist. Soc. Ser. B , vol.70 , pp. 371-388
    • MOLENBERGHS, G.1    BEUNCKENS, C.2    SOTTO, C.3    KEN-WARD, M.G.4
  • 49
    • 0035650307 scopus 로고    scopus 로고
    • Sensitivity analysis for incomplete contingency tables: The Slovenian plebiscite case
    • MOLENBERGHS, G., KENWARD, M. G. and GOETGHEBEUR, E. (2001). Sensitivity analysis for incomplete contingency tables: the Slovenian plebiscite case. Appl. Statist. 50 15-29.
    • (2001) Appl. Statist , vol.50 , pp. 15-29
    • MOLENBERGHS, G.1    KENWARD, M.G.2    GOETGHEBEUR, E.3
  • 50
    • 0032353609 scopus 로고    scopus 로고
    • Pseudo-likelihood for combined selection and patternmixture models for missing data problems
    • MOLENBERGHS, G., MICHIELS, B. and KENWARD, M. G. (1998). Pseudo-likelihood for combined selection and patternmixture models for missing data problems. Biometrical J. 40 557-572.
    • (1998) Biometrical J , vol.40 , pp. 557-572
    • MOLENBERGHS, G.1    MICHIELS, B.2    KENWARD, M.G.3
  • 53
    • 50849087543 scopus 로고    scopus 로고
    • MOLENBERGHS, G. and VERBEKE, G. (2005). Models for Discrete Longitudinal Data. Springer, New York. MR2171048
    • MOLENBERGHS, G. and VERBEKE, G. (2005). Models for Discrete Longitudinal Data. Springer, New York. MR2171048
  • 54
    • 0035963906 scopus 로고    scopus 로고
    • Mastitis in dairy cattle: Influence analysis to assess sensitivity of the dropout process
    • MR1862482
    • MOLENBERGHS, G., VERBEKE, G., THIJS, H., LESAFFRE, E. and KENWARD, M. G. (2001). Mastitis in dairy cattle: Influence analysis to assess sensitivity of the dropout process. Comput. Statist. Data Anal. 37 93-113. MR1862482
    • (2001) Comput. Statist. Data Anal , vol.37 , pp. 93-113
    • MOLENBERGHS, G.1    VERBEKE, G.2    THIJS, H.3    LESAFFRE, E.4    KENWARD, M.G.5
  • 55
    • 0001010853 scopus 로고
    • On structural equation modeling with data that are not missing completely at random
    • MUTHÉN, B., KAPLAN, D. and HOLLIS, M. (1987). On structural equation modeling with data that are not missing completely at random. Psychometrika 52 431-462.
    • (1987) Psychometrika , vol.52 , pp. 431-462
    • MUTHÉN, B.1    KAPLAN, D.2    HOLLIS, M.3
  • 56
    • 84950953410 scopus 로고
    • Inference from nonrandomly missing categorical data: An example from a genetic study on Turner's syndrome
    • NORDHEIM, E. V. (1984). Inference from nonrandomly missing categorical data: An example from a genetic study on Turner's syndrome. J. Amer. Statistic. Assoc. 79 772-780.
    • (1984) J. Amer. Statistic. Assoc , vol.79 , pp. 772-780
    • NORDHEIM, E.V.1
  • 57
    • 0000661332 scopus 로고
    • A generalized multivariate analysis of variance model useful especially for growth curve problems
    • MR0181062
    • POTTHOFF, R. F. and ROY, S. N. (1964). A generalized multivariate analysis of variance model useful especially for growth curve problems. Biometrika 51 313-326. MR0181062
    • (1964) Biometrika , vol.51 , pp. 313-326
    • POTTHOFF, R.F.1    ROY, S.N.2
  • 59
    • 50849084319 scopus 로고    scopus 로고
    • Sensitivity analysis in pattern mixture models using the extrapolation method
    • Submitted for publication
    • RIZOPOULOS, D., VERBEKE, G. and LESAFFRE, E. (2007). Sensitivity analysis in pattern mixture models using the extrapolation method. Submitted for publication.
    • (2007)
    • RIZOPOULOS, D.1    VERBEKE, G.2    LESAFFRE, E.3
  • 60
    • 40249113335 scopus 로고    scopus 로고
    • Shared parameter models under random-effects misspecification
    • RIZOPOULOS, D., VERBEKE, G. and MOLENBERGHS, G. (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
  • 61
    • 21844487694 scopus 로고
    • Semiparametric efficiency in multivariate regression models with missing data
    • MR1325119
    • ROBINS, J. M. and ROTNITZKY, A. (1995). Semiparametric efficiency in multivariate regression models with missing data. J. Amer. Statist. Assoc. 90 122-129. MR1325119
    • (1995) J. Amer. Statist. Assoc , vol.90 , pp. 122-129
    • ROBINS, J.M.1    ROTNITZKY, A.2
  • 62
    • 0032264836 scopus 로고    scopus 로고
    • Semiparametric regression for repeated outcomes with non-ignorable non-response
    • MR1666631
    • ROBINS, J. M., ROTNITZKY, A. and SCHARFSTEIN, D. O. (1998). Semiparametric regression for repeated outcomes with non-ignorable non-response. J. Amer. Statist. Assoc. 93 1321-1339. MR1666631
    • (1998) J. Amer. Statist. Assoc , vol.93 , pp. 1321-1339
    • ROBINS, J.M.1    ROTNITZKY, A.2    SCHARFSTEIN, D.O.3
  • 63
    • 50849134474 scopus 로고    scopus 로고
    • ROBINS, J. M., ROTNITZKY, A. and SCHARFSTEIN, D. O. (2000). Sensitivity analysis for selection bias and unmeasured confounding in missing data and causal inference models. In Statistical Models in Epidemiology, the Environment, and Clinical Trials (M. E. Halloran and D. A. Berry, eds.) 1-94. Springer, New York. MR1731681
    • ROBINS, J. M., ROTNITZKY, A. and SCHARFSTEIN, D. O. (2000). Sensitivity analysis for selection bias and unmeasured confounding in missing data and causal inference models. In Statistical Models in Epidemiology, the Environment, and Clinical Trials (M. E. Halloran and D. A. Berry, eds.) 1-94. Springer, New York. MR1731681
  • 64
    • 84888862680 scopus 로고
    • Estimation of regression coefficients when some regressors are not always observed
    • MR1294730
    • ROBINS, J. M., ROTNITZKY, A. and ZHAO, L. P. (1994). Estimation of regression coefficients when some regressors are not always observed. J. Amer. Statist. Assoc. 89 846-866. MR1294730
    • (1994) J. Amer. Statist. Assoc , vol.89 , pp. 846-866
    • ROBINS, J.M.1    ROTNITZKY, A.2    ZHAO, L.P.3
  • 65
    • 77951622706 scopus 로고
    • The central role of the propensity score method in observational studies for causal effects
    • MR0742974
    • ROSENBAUM, P. R. and RUBIN, D. B. (1983). The central role of the propensity score method in observational studies for causal effects. Biometrika 70 41-55. MR0742974
    • (1983) Biometrika , vol.70 , pp. 41-55
    • ROSENBAUM, P.R.1    RUBIN, D.B.2
  • 66
    • 0035102566 scopus 로고    scopus 로고
    • Methods for conducting sensitivity analysis of trials with potentially nonignorable competing causes of censoring
    • MR1833295
    • ROTNITZKY, A., SCHARFSTEIN, D., SU, T. L. and ROBINS, J. M. (2001). Methods for conducting sensitivity analysis of trials with potentially nonignorable competing causes of censoring. Biometrics 57 103-113. MR1833295
    • (2001) Biometrics , vol.57 , pp. 103-113
    • ROTNITZKY, A.1    SCHARFSTEIN, D.2    SU, T.L.3    ROBINS, J.M.4
  • 67
    • 0017133178 scopus 로고
    • Inference and missing data
    • MR0455196
    • RUBIN, D. B. (1976). Inference and missing data. Biometrika 63 581-592. MR0455196
    • (1976) Biometrika , vol.63 , pp. 581-592
    • RUBIN, D.B.1
  • 68
    • 50849086277 scopus 로고    scopus 로고
    • RUBIN, D. B. (1987). Multiple Imputation for Nonresponse in Surveys. Wiley, New York. MR0899519
    • RUBIN, D. B. (1987). Multiple Imputation for Nonresponse in Surveys. Wiley, New York. MR0899519
  • 69
    • 50849085017 scopus 로고    scopus 로고
    • RUBIN, D. B. (1994). Discussion of Informative dropout in longitudinal data analysis, by P. J. Diggle and M. G. Kenward. Appl. Statist. 43 80-82.
    • RUBIN, D. B. (1994). Discussion of "Informative dropout in longitudinal data analysis," by P. J. Diggle and M. G. Kenward. Appl. Statist. 43 80-82.
  • 70
    • 84950419706 scopus 로고
    • Handling "don't know" survey responses: The case of the Slovenian plebiscite
    • RUBIN, D. B., STERN, H. S. and VEHOVAR, V. (1995). Handling "don't know" survey responses: The case of the Slovenian plebiscite. J. Amer. Statist. Assoc. 90 822-828.
    • (1995) J. Amer. Statist. Assoc , vol.90 , pp. 822-828
    • RUBIN, D.B.1    STERN, H.S.2    VEHOVAR, V.3
  • 71
    • 0442278084 scopus 로고    scopus 로고
    • Adjusting for nonignorable drop-out using semiparametric nonresponse models (with discussion)
    • MR1731478
    • SCHARFSTEIN, D. O., ROTNITZKY, A. and ROBINS, J. M. (1999). Adjusting for nonignorable drop-out using semiparametric nonresponse models (with discussion). J. Amer. Statist. Assoc. 94 1096-1146. MR1731478
    • (1999) J. Amer. Statist. Assoc , vol.94 , pp. 1096-1146
    • SCHARFSTEIN, D.O.1    ROTNITZKY, A.2    ROBINS, J.M.3
  • 73
    • 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 J. 42 617-646.
    • (2000) Biometrical J , vol.42 , pp. 617-646
    • THIJS, H.1    MOLENBERGHS, G.2    VERBEKE, G.3
  • 74
    • 0039982650 scopus 로고    scopus 로고
    • Analysis of longitudinal data with non-ignorable non-monotone missing values
    • TROXEL, A. B., HARRINGTON, D. P. and LIPSITZ, S. R. (1998). Analysis of longitudinal data with non-ignorable non-monotone missing values. Appl. Statist. 47 425-438.
    • (1998) Appl. Statist , vol.47 , pp. 425-438
    • TROXEL, A.B.1    HARRINGTON, D.P.2    LIPSITZ, S.R.3
  • 75
    • 50849137019 scopus 로고    scopus 로고
    • A semiparametric shared parameter model to handle non-monotone non-ignorable missingness
    • Submitted for publication
    • TSONAKA, R., VERBEKE, G. and LESAFFRE, E. (2007). A semiparametric shared parameter model to handle non-monotone non-ignorable missingness. Submitted for publication.
    • (2007)
    • TSONAKA, R.1    VERBEKE, G.2    LESAFFRE, E.3
  • 76
    • 0029048659 scopus 로고
    • Logistic regression with incompletely observed categorical covariates-investigating the sensitivity against violation of the missing at random assumption
    • VACH, W. and BLETTNER, M. (1995). Logistic regression with incompletely observed categorical covariates-investigating the sensitivity against violation of the missing at random assumption. Statistics in Medicine 12 1315-1330.
    • (1995) Statistics in Medicine , vol.12 , pp. 1315-1330
    • VACH, W.1    BLETTNER, M.2
  • 77
    • 33750348204 scopus 로고    scopus 로고
    • Ignorance and uncertainty regions as inferential tools in a sensitivity analysis
    • MR2281311
    • VANSTEELANDT, S., GOETGHEBEUR, E., KENWARD, M. G. and MOLENBERGHS, G. (2006). Ignorance and uncertainty regions as inferential tools in a sensitivity analysis. Statist. Sinica 16 953-979. MR2281311
    • (2006) Statist. Sinica , vol.16 , pp. 953-979
    • VANSTEELANDT, S.1    GOETGHEBEUR, E.2    KENWARD, M.G.3    MOLENBERGHS, G.4
  • 78
  • 79
    • 0034994805 scopus 로고    scopus 로고
    • The practical use of different strategies to handle dropout in longitudinal studies
    • VERBEKE, G., LESAFFRE, E. and SPIESSENS, B. (2001). The practical use of different strategies to handle dropout in longitudinal studies. Drug Information J. 35 419-434.
    • (2001) Drug Information J , vol.35 , pp. 419-434
    • VERBEKE, G.1    LESAFFRE, E.2    SPIESSENS, B.3
  • 80
    • 0001425197 scopus 로고    scopus 로고
    • Linear Mixed Models in Practice: A SAS-Oriented Approach
    • Springer, New York
    • VERBEKE, G. and MOLENBERGHS, G. (1997). Linear Mixed Models in Practice: A SAS-Oriented Approach. Lecture Notes in Statist. 126. Springer, New York.
    • (1997) Lecture Notes in Statist , vol.126
    • VERBEKE, G.1    MOLENBERGHS, G.2
  • 81
    • 50849137683 scopus 로고    scopus 로고
    • VERBEKE, G. and MOLENBERGHS, G. (2000). Linear Mixed Models for Longitudinal Data. Springer, New York. MR1880596
    • VERBEKE, G. and MOLENBERGHS, G. (2000). Linear Mixed Models for Longitudinal Data. Springer, New York. MR1880596
  • 82
    • 0035102436 scopus 로고    scopus 로고
    • Sensitivity analysis for nonrandom dropout: A local influence approach
    • MR1833286
    • VERBEKE, G., MOLENBERGHS, G., THIJS, H., LESAFFRE, E. and KENWARD, M. G. (2001). Sensitivity analysis for nonrandom dropout: A local influence approach. Biometrics 57 7-14. MR1833286
    • (2001) Biometrics , vol.57 , pp. 7-14
    • VERBEKE, G.1    MOLENBERGHS, G.2    THIJS, H.3    LESAFFRE, E.4    KENWARD, M.G.5
  • 83
    • 0023779040 scopus 로고
    • Analysing changes in the presence of informative right censoring caused by death and withdrawal
    • WU, M. C. and BAILEY, K. R. (1988). Analysing changes in the presence of informative right censoring caused by death and withdrawal. Statistics in Medicine 7 337-346.
    • (1988) Statistics in Medicine , vol.7 , pp. 337-346
    • WU, M.C.1    BAILEY, K.R.2
  • 84
    • 0024438062 scopus 로고
    • Estimation and comparison of changes in the presence of informative right censoring: Conditional linear model
    • MR1029611
    • WU, M. C. and BAILEY, K. R. (1989). Estimation and comparison of changes in the presence of informative right censoring: Conditional linear model. Biometrics 45 939-955. MR1029611
    • (1989) Biometrics , vol.45 , pp. 939-955
    • WU, M.C.1    BAILEY, K.R.2
  • 85
    • 0023921412 scopus 로고
    • Estimation and comparison of changes in the presence of informative right censoring by modeling the censoring process
    • MR0931633
    • 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. MR0931633
    • (1988) Biometrics , vol.44 , pp. 175-188
    • WU, M.C.1    CARROLL, R.J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.