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Volumn 23, Issue 1, 2014, Pages 60-73

Dropout in crossover and longitudinal studies: Is complete case so bad?

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; CLINICAL TRIAL (TOPIC); CROSSOVER PROCEDURE; HUMAN; LONGITUDINAL STUDY; PATIENT DROPOUTS; PROBABILITY; RANDOMIZATION; SIDE EFFECT; TIME;

EID: 84892607657     PISSN: 09622802     EISSN: 14770334     Source Type: Journal    
DOI: 10.1177/0962280212445838     Document Type: Article
Times cited : (8)

References (37)
  • 1
    • 0023716933 scopus 로고
    • Missing data in longitudinal studies
    • Laird NM. Missing data in longitudinal studies. Stat Med. 1988 ; 7: 305-315
    • (1988) Stat Med , vol.7 , pp. 305-315
    • Laird, N.M.1
  • 2
    • 84950452119 scopus 로고
    • Modeling the dropout mechanism in repeated-measures studies
    • Little RJA. Modeling the dropout mechanism in repeated-measures studies. J Am Stat Assoc. 1995 ; 90: 1112-1121
    • (1995) J Am Stat Assoc , vol.90 , pp. 1112-1121
    • Little, R.J.A.1
  • 3
    • 10644222277 scopus 로고    scopus 로고
    • Analyzing incomplete longitudinal clinical trial data
    • Molenberghs G, Thijs H, Jansen I, et al. Analyzing incomplete longitudinal clinical trial data. Biostatistics. 2004 ; 5: 445-464
    • (2004) Biostatistics , vol.5 , pp. 445-464
    • Molenberghs, G.1    Thijs, H.2    Jansen, I.3
  • 6
    • 63249128252 scopus 로고    scopus 로고
    • Comparative review of methods for handling drop-out in longitudinal studies
    • Philipson PM, Ho W-K, Henderson R. Comparative review of methods for handling drop-out in longitudinal studies. Stat Med. 2008 ; 27: 6276-6298
    • (2008) Stat Med , vol.27 , pp. 6276-6298
    • Philipson, P.M.1    Ho, W.-K.2    Henderson, R.3
  • 9
    • 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, et al. Every missingness not at random model has a missingness at random counterpart with equal fit. J Roy Stat Soc Ser B. 2008 ; 70: 371-388
    • (2008) J Roy Stat Soc ser B , vol.70 , pp. 371-388
    • Molenberghs, G.1    Beunckens, C.2    Sotto, C.3
  • 10
    • 0031014353 scopus 로고    scopus 로고
    • Non-response models for the analysis of non-monotone ignorable missing data
    • Robins J, Gill R. Non-response models for the analysis of non-monotone ignorable missing data. Stat Med. 1997 ; 16: 39-56
    • (1997) Stat Med , vol.16 , pp. 39-56
    • Robins, J.1    Gill, R.2
  • 11
    • 34848824770 scopus 로고    scopus 로고
    • Analysis of longitudinal data with drop-out: Objectives, assumptions and a proposal (with discussion)
    • Diggle P, Farewell D, Henderson R. Analysis of longitudinal data with drop-out: objectives, assumptions and a proposal (with discussion). Appl Stat. 2007 ; 56: 499-550
    • (2007) Appl Stat , vol.56 , pp. 499-550
    • Diggle, P.1    Farewell, D.2    Henderson, R.3
  • 12
    • 77956647053 scopus 로고    scopus 로고
    • A dynamic approach for reconstructing missing longitudinal data using the linear increments model
    • Aalen O, Gunnes N. A dynamic approach for reconstructing missing longitudinal data using the linear increments model. Biostatistics. 2010 ; 11: 453-472
    • (2010) Biostatistics , vol.11 , pp. 453-472
    • Aalen, O.1    Gunnes, N.2
  • 13
    • 0019272058 scopus 로고
    • Terminology-A plea for standardization
    • Meinert C. Terminology-a plea for standardization. Control Clin Trial. 1980 ; 1 (2). 97-97
    • (1980) Control Clin Trial , vol.1 , Issue.2 , pp. 97-97
    • Meinert, C.1
  • 14
    • 3242768440 scopus 로고    scopus 로고
    • Analysis of longitudinal studies with death and drop-out:A case study
    • Dufoil C, Brayne D, Clayton D. Analysis of longitudinal studies with death and drop-out:a case study. Stat Med. 2004 ; 23: 2215-2226
    • (2004) Stat Med , vol.23 , pp. 2215-2226
    • Dufoil, C.1    Brayne, D.2    Clayton, D.3
  • 15
    • 84892607773 scopus 로고    scopus 로고
    • Discussion of: Analysis of longitudinal data with drop-out: Objectives, assumptions and a proposal (by P. Diggle, D. Farewell and R. Henderson)
    • Didelez V. Discussion of: Analysis of longitudinal data with drop-out: objectives, assumptions and a proposal (by P. Diggle, D. Farewell and R. Henderson). Appl Stat. 2007 ; 56: 536-537
    • (2007) Appl Stat , vol.56 , pp. 536-537
    • Didelez, V.1
  • 16
    • 58149417330 scopus 로고
    • Estimating causal effects of treatments in randomized and nonrandomized studies
    • Rubin D. Estimating causal effects of treatments in randomized and nonrandomized studies. J Educ Psychol. 1974 ; 66 (5). 688-688
    • (1974) J Educ Psychol , vol.66 , Issue.5 , pp. 688-688
    • Rubin, D.1
  • 17
    • 78650231015 scopus 로고    scopus 로고
    • Generalized pairwise comparisons of prioritized outcomes in the two-sample problem
    • Buyse M. Generalized pairwise comparisons of prioritized outcomes in the two-sample problem. Stat Med. 2010 ; 29: 3245-3257
    • (2010) Stat Med , vol.29 , pp. 3245-3257
    • Buyse, M.1
  • 18
    • 33745037252 scopus 로고    scopus 로고
    • A comparison of multiple imputation and doubly robust estimation for analyses with missing data
    • Carpenter JR, Kenward MG, Vansteelandt S. A comparison of multiple imputation and doubly robust estimation for analyses with missing data. J Roy Stat Soc Ser A. 2006 ; 169: 571-584
    • (2006) J Roy Stat Soc ser A , vol.169 , pp. 571-584
    • Carpenter, J.R.1    Kenward, M.G.2    Vansteelandt, S.3
  • 19
    • 4243828610 scopus 로고
    • Informative drop-out in longitudinal data analysis (with discussion)
    • Diggle PJ, Kenward MG. Informative drop-out in longitudinal data analysis (with discussion). Appl Stat. 1994 ; 43: 49-93
    • (1994) Appl Stat , vol.43 , pp. 49-93
    • Diggle, P.J.1    Kenward, M.G.2
  • 20
    • 21144483152 scopus 로고
    • Pattern mixture models for multivariate incomplete data
    • Little RJA. Pattern mixture models for multivariate incomplete data. J Am Stat Assoc. 1993 ; 88: 125-134
    • (1993) J Am Stat Assoc , vol.88 , pp. 125-134
    • Little, R.J.A.1
  • 21
    • 77249123881 scopus 로고    scopus 로고
    • Marginal analyses of longitudinal data with an informative pattern of observations
    • Farewell DM. Marginal analyses of longitudinal data with an informative pattern of observations. Biometrika. 2010 ; 97: 65-78
    • (2010) Biometrika , vol.97 , pp. 65-78
    • Farewell, D.M.1
  • 22
    • 84950421496 scopus 로고
    • Analysis of semiparametric regression-models for repeated outcomes in the presence of missing data
    • Robins JM, Rotnitzky A, Zhao LP. Analysis of semiparametric regression-models for repeated outcomes in the presence of missing data. J Am Stat Assoc. 1995 ; 90: 106-121
    • (1995) J Am Stat Assoc , vol.90 , pp. 106-121
    • Robins, J.M.1    Rotnitzky, A.2    Zhao, L.P.3
  • 23
    • 21844487694 scopus 로고
    • Semiparametric efficiency in multivariate regression-models with missing data
    • Robins JM, Rotnitzky A. Semiparametric efficiency in multivariate regression-models with missing data. J Am Stat Assoc. 1995 ; 90: 122-129
    • (1995) J Am Stat Assoc , vol.90 , pp. 122-129
    • Robins, J.M.1    Rotnitzky, A.2
  • 24
    • 0032264836 scopus 로고    scopus 로고
    • Semiparametric regression for repeated out-comes with nonignorable nonresponse
    • Rotnitzky A, Robins JM, Scharfstein DO. Semiparametric regression for repeated out-comes with nonignorable nonresponse. J Am Stat Assoc. 1998 ; 93: 1321-1339
    • (1998) J Am Stat Assoc , vol.93 , pp. 1321-1339
    • Rotnitzky, A.1    Robins, J.M.2    Scharfstein, D.O.3
  • 25
    • 0035102566 scopus 로고    scopus 로고
    • Methods for conducting sensitivity analysis of trials with potentially non-ignorable competing causes of censoring
    • Rotnitzky A, Scharfstein DO, Su TL, et al. Methods for conducting sensitivity analysis of trials with potentially non-ignorable competing causes of censoring. Biometrics. 2001 ; 57: 103-112
    • (2001) Biometrics , vol.57 , pp. 103-112
    • Rotnitzky, A.1    Scharfstein, D.O.2    Su, T.L.3
  • 26
    • 0442278084 scopus 로고    scopus 로고
    • Adjusting for non-ignorable drop-out using semiparametric non-response models (with discussion)
    • Scharfstein DO, Rotnitzky A, Robins JM. Adjusting for non-ignorable drop-out using semiparametric non-response models (with discussion). J Am Stat Assoc. 1999 ; 94: 1096-1146
    • (1999) J Am Stat Assoc , vol.94 , pp. 1096-1146
    • Scharfstein, D.O.1    Rotnitzky, A.2    Robins, J.M.3
  • 27
    • 2942658011 scopus 로고    scopus 로고
    • Incorporating prior beliefs about selection bias into the analysis of randomized trials with missing outcomes
    • Scharfstein DO, Daniels M, Robins JM. Incorporating prior beliefs about selection bias into the analysis of randomized trials with missing outcomes. Biostatistics. 2003 ; 4: 495-512
    • (2003) Biostatistics , vol.4 , pp. 495-512
    • Scharfstein, D.O.1    Daniels, M.2    Robins, J.M.3
  • 28
    • 39549121035 scopus 로고    scopus 로고
    • Allowing for uncertainty due to missing data in meta analysis-part 1: Two-stage methods
    • White IR, Higgins JP, Wood AM. Allowing for uncertainty due to missing data in meta analysis-part 1: two-stage methods. Stat Med. 2008 ; 27: 711-727
    • (2008) Stat Med , vol.27 , pp. 711-727
    • White, I.R.1    Higgins, J.P.2    Wood, A.M.3
  • 30
    • 85057445352 scopus 로고    scopus 로고
    • Fitzmaurice G Davidian M Verbeke G Molenberghs G, ed. Boca Raton: Chapman and Hall/CRC Press
    • Little R Longitudinal data analysis. Fitzmaurice G Davidian M Verbeke G Molenberghs G, ed. Boca Raton: Chapman and Hall/CRC Press ; 2008: 409-432.
    • (2008) Longitudinal Data Analysis , pp. 409-432
    • Little, R.1
  • 31
    • 84864018660 scopus 로고    scopus 로고
    • Armitage lecture 2010: Understanding treatment effects: The value of integrating longitudinal data and survival analysis
    • Aalen OO. Armitage lecture 2010: Understanding treatment effects: the value of integrating longitudinal data and survival analysis. Stat Med. 2012 ;:
    • (2012) Stat Med
    • Aalen, O.O.1
  • 33
    • 8644246036 scopus 로고    scopus 로고
    • Joint modeling of longitudinal and time-to-event data: An overview
    • Tsiatis A, Davidian M. Joint modeling of longitudinal and time-to-event data: an overview. Stat Sin. 2004 ; 14 (3). 809-834
    • (2004) Stat Sin , vol.14 , Issue.3 , pp. 809-834
    • Tsiatis, A.1    Davidian, M.2
  • 34
    • 38949107918 scopus 로고    scopus 로고
    • Comparison of analgesic effects and patient tolerability of nabilone and dihydrocodeine for chronic neuropathic pain: Randomised, crossover, double blind study
    • Frank B, Serpell MG, Hughes J, et al. Comparison of analgesic effects and patient tolerability of nabilone and dihydrocodeine for chronic neuropathic pain: randomised, crossover, double blind study. Br Med J. 2008 ; 336: 199-201
    • (2008) Br Med J , vol.336 , pp. 199-201
    • Frank, B.1    Serpell, M.G.2    Hughes, J.3
  • 36
    • 0002019758 scopus 로고    scopus 로고
    • Hidden truncation models
    • Arnold BC, Beaver RJ. Hidden truncation models. Sankhyā A. 2000 ; 62: 23-35
    • (2000) Sankhyā A , vol.62 , pp. 23-35
    • Arnold, B.C.1    Beaver, R.J.2
  • 37
    • 77956890002 scopus 로고
    • A class of pattern-mixture models for normal incomplete data
    • Little RJA. A class of pattern-mixture models for normal incomplete data. Biometrika. 1994 ; 81: 471-483
    • (1994) Biometrika , vol.81 , pp. 471-483
    • Little, R.J.A.1


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