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Volumn , Issue , 2012, Pages 1-345

Multiple Imputation and its Application

Author keywords

[No Author keywords available]

Indexed keywords

BEHAVIORAL RESEARCH; DATA STRUCTURES;

EID: 84949747578     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1002/9781119942283     Document Type: Book
Times cited : (723)

References (192)
  • 1
    • 0000828942 scopus 로고
    • Missing observations in multivariate statistics I: Review of the literature
    • Afifi, A. and Elashoff, R. (1966) Missing observations in multivariate statistics I: Review of the literature. Journal of the American Statistical Association, 61, 595-604.
    • (1966) Journal of the American Statistical Association , vol.61 , pp. 595-604
    • Afifi, A.1    Elashoff, R.2
  • 2
    • 0141712557 scopus 로고
    • Polychotomous quantal response by maximum indicant
    • Aitchison, J. and Bennett, J. A. (1970) Polychotomous quantal response by maximum indicant. Biometrika, 57, 253-262.
    • (1970) Biometrika , vol.57 , pp. 253-262
    • Aitchison, J.1    Bennett, J.A.2
  • 4
    • 85017468853 scopus 로고    scopus 로고
    • Shared parameter models
    • (Eds M. Davidian, G. Fitzmaurice, G. Molenberghs and G. Verbeke), Chapman & Hall/CRC
    • Albert, P. S. and Follman, D. A. (2009) Shared parameter models. In Longitudinal Data Analysis: A Handbook of Modern Statistical Methods (Eds M. Davidian, G. Fitzmaurice, G. Molenberghs and G. Verbeke), pp. 433-452. Chapman & Hall/CRC.
    • (2009) Longitudinal Data Analysis: A Handbook of Modern Statistical Methods , pp. 433-452
    • Albert, P.S.1    Follman, D.A.2
  • 5
  • 6
  • 8
    • 0002881703 scopus 로고
    • A representation of the joint distribution of responses to n dichotomous items
    • (Ed. H. Solomon). Stanford, CA: 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 (Ed. H. Solomon). Stanford, CA: Stanford University Press.
    • (1961) Studies in Item Analysis and Prediction
    • Bahadur, R.R.1
  • 9
    • 33644851650 scopus 로고    scopus 로고
    • Doubly robust estimation in missing data and causal inference models
    • Bang, H. and Robins, J. M. (2005) Doubly robust estimation in missing data and causal inference models. Biometrics, 61, 962-973.
    • (2005) Biometrics , vol.61 , pp. 962-973
    • Bang, H.1    Robins, J.M.2
  • 10
    • 2442736478 scopus 로고    scopus 로고
    • Small-sample degrees of freedom with multiple imputation
    • Barnard, J. and Rubin, D. B. (1999) Small-sample degrees of freedom with multiple imputation. Biometrika, 86, 948-955.
    • (1999) Biometrika , vol.86 , pp. 948-955
    • Barnard, J.1    Rubin, D.B.2
  • 11
    • 70349245594 scopus 로고    scopus 로고
    • Successes, challenges, and limitations of current antiretroviral therapy in low-income and middle-income countries
    • Bartlett, J. A. and Shao, J. F. (2009) Successes, challenges, and limitations of current antiretroviral therapy in low-income and middle-income countries. Lanced Infectious Diseases, 9, 637-649.
    • (2009) Lanced Infectious Diseases , vol.9 , pp. 637-649
    • Bartlett, J.A.1    Shao, J.F.2
  • 13
    • 84949884464 scopus 로고    scopus 로고
    • Accommodating the model of interest within the fully conditional specification multiple imputation framework
    • Bartlett, J. W., Seaman, S., White, I. R. and Carpenter, J. R. (2012) Accommodating the model of interest within the fully conditional specification multiple imputation framework. Submitted.
    • (2012) Submitted
    • Bartlett, J.W.1    Seaman, S.2    White, I.R.3    Carpenter, J.R.4
  • 14
    • 33847711413 scopus 로고    scopus 로고
    • Robustness of a multivariate normal approximation for imputation of incomplete binary data
    • Bernaards, C. A., Belin, T. R. and Schafer, J. L. (2007) Robustness of a multivariate normal approximation for imputation of incomplete binary data. Statistics in Medicine, 26, 1368-1382.
    • (2007) Statistics in Medicine , vol.26 , pp. 1368-1382
    • Bernaards, C.A.1    Belin, T.R.2    Schafer, J.L.3
  • 17
    • 84872165791 scopus 로고    scopus 로고
    • Practical considerations for sensitivity analysis after multiple imputation applied to epidemiological studies with incomplete data
    • Bousquet, A. H., Desenclos, J. C., Larsen, C., Le Strat, Y. and Carpenter, J. R. (2012) Practical considerations for sensitivity analysis after multiple imputation applied to epidemiological studies with incomplete data. BMC Medical Research Methodology, 12, 73.
    • (2012) BMC Medical Research Methodology , vol.12 , pp. 73
    • Bousquet, A.H.1    Desenclos, J.C.2    Larsen, C.3    Le Strat, Y.4    Carpenter, J.R.5
  • 18
    • 77951765385 scopus 로고
    • A saturated model for analyzing exchangeable binary data: applications to clinical and developmental toxicity studies
    • Bowman, D. and George, E. O. (1995) A saturated model for analyzing exchangeable binary data: applications to clinical and developmental toxicity studies. Journal of the American Statistical Association, 90, 871-879.
    • (1995) Journal of the American Statistical Association , vol.90 , pp. 871-879
    • Bowman, D.1    George, E.O.2
  • 20
    • 67149102150 scopus 로고    scopus 로고
    • Lost to follow-up in antiretroviral treatment programmes in resource-limited settings: systematic review and meta-analysis
    • Brinkhof, M. W. G., Pujades-Rodreguez, M. and Egger, M. (2009) Lost to follow-up in antiretroviral treatment programmes in resource-limited settings: systematic review and meta-analysis. PLOS ONE, 4, e5790.
    • (2009) PLOS ONE , vol.4 , pp. e5790
    • Brinkhof, M.W.G.1    Pujades-Rodreguez, M.2    Egger, M.3
  • 22
    • 30144445854 scopus 로고    scopus 로고
    • MCMC algorithms for constrained variance matrices
    • Browne, W. J. (2006) MCMC algorithms for constrained variance matrices. Computational Statistics and Data Analysis, 50, 1655-1677.
    • (2006) Computational Statistics and Data Analysis , vol.50 , pp. 1655-1677
    • Browne, W.J.1
  • 23
    • 0031958895 scopus 로고    scopus 로고
    • Budesonide delivered by Turbuhaler is effective in a dosedependent fashion when used in the treatment of adult patients with chronic asthma
    • Busse, W. W., Chervinsky, P., Condemi, J., Lumry, W. R., Petty, T. L., Rennard, S. and Townley, R. G. (1998) Budesonide delivered by Turbuhaler is effective in a dosedependent fashion when used in the treatment of adult patients with chronic asthma. Journal of Allergy and Clinical Immunology, 101, 457-463.
    • (1998) Journal of Allergy and Clinical Immunology , vol.101 , pp. 457-463
    • Busse, W.W.1    Chervinsky, P.2    Condemi, J.3    Lumry, W.R.4    Petty, T.L.5    Rennard, S.6    Townley, R.G.7
  • 24
    • 84856274182 scopus 로고    scopus 로고
    • REALCOM-IMPUTE software for multilevel multiple imputation with mixed response types
    • Carpenter, J. R., Goldstein, H. and Kenward, M. G. (2011a) REALCOM-IMPUTE software for multilevel multiple imputation with mixed response types. Journal of Statistical Software, 45(4), 1-14.
    • (2011) Journal of Statistical Software , vol.45 , Issue.4 , pp. 1-14
    • Carpenter, J.R.1    Goldstein, H.2    Kenward, M.G.3
  • 26
    • 84949773921 scopus 로고    scopus 로고
    • Statistical modelling of partially observed data using multiple imputation: principles and practice
    • Eds Y. Tu and D. Greenwood, New York:Springer
    • Carpenter, J. R., Kenward, M. G. and Goldstein, H. (2012) Statistical modelling of partially observed data using multiple imputation: principles and practice. In Modern Methods for Epidemiology (Eds Y. Tu and D. Greenwood), pp. 15-31. New York:Springer.
    • (2012) Modern Methods for Epidemiology , pp. 15-31
    • Carpenter, J.R.1    Kenward, M.G.2    Goldstein, H.3
  • 28
    • 34347398256 scopus 로고    scopus 로고
    • Sensitivity analysis after multiple imputation under missing at random - a weighting approach
    • Carpenter, J. R., Kenward, M. G. andWhite, I. R. (2007) Sensitivity analysis after multiple imputation under missing at random - a weighting approach. Statistical Methods in Medical Research, 16, 259-275.
    • (2007) Statistical Methods in Medical Research , vol.16 , pp. 259-275
    • Carpenter, J.R.1    Kenward, M.G.2    White, I.R.3
  • 29
    • 84896321989 scopus 로고    scopus 로고
    • Analysing longitudinal studies with non-response:issues and statistical methods
    • Eds M. Williams and P. Vogt, London: SAGE
    • Carpenter, J. R. and Plewis, I. (2011) Analysing longitudinal studies with non-response:issues and statistical methods. In The SAGE Handbook of Innovation in Social Research Methods (Eds M. Williams and P. Vogt), London: SAGE.
    • (2011) The SAGE Handbook of Innovation in Social Research Methods
    • Carpenter, J.R.1    Plewis, I.2
  • 30
    • 0037197598 scopus 로고    scopus 로고
    • Coping with missing data in clinical trials: a model based approach applied to asthma trials
    • Carpenter, J. R., Pocock, S. and Lamm, C. J. (2002) Coping with missing data in clinical trials: a model based approach applied to asthma trials. Statistics in Medicine, 21, 1043-1066.
    • (2002) Statistics in Medicine , vol.21 , pp. 1043-1066
    • Carpenter, J.R.1    Pocock, S.2    Lamm, C.J.3
  • 31
    • 84887005678 scopus 로고    scopus 로고
    • Analysis of longitudinal trials with missing data: a framework for relevant accessible assumptions and inference via multiple imputation
    • in press
    • Carpenter, J. R., Roger, J. H. and Kenward, M. G. (2013) Analysis of longitudinal trials with missing data: a framework for relevant accessible assumptions and inference via multiple imputation. Journal of Biopharmaceutical Statistics, in press.
    • (2013) Journal of Biopharmaceutical Statistics
    • Carpenter, J.R.1    Roger, J.H.2    Kenward, M.G.3
  • 32
    • 80052819432 scopus 로고    scopus 로고
    • Assessing the sensitivity of metaanalysis to selection bias: a multiple imputation approach
    • Carpenter, J. R., Rücker, G. and Schwarzer, G. (2011b) Assessing the sensitivity of metaanalysis to selection bias: a multiple imputation approach. Biometrics, 67, 1066-1072.
    • (2011) Biometrics , vol.67 , pp. 1066-1072
    • Carpenter, J.R.1    Rücker, G.2    Schwarzer, G.3
  • 33
    • 0000911137 scopus 로고    scopus 로고
    • Analysis of multivariate probit models
    • Chib, S. and Greenburg, E. (1998) Analysis of multivariate probit models. Biometrika, 85, 347-361.
    • (1998) Biometrika , vol.85 , pp. 347-361
    • Chib, S.1    Greenburg, E.2
  • 34
    • 4344570142 scopus 로고    scopus 로고
    • Practical introduction to record linkage for injury research
    • Clark, D. (2004) Practical introduction to record linkage for injury research. Injury Prevention, 10, 186-191.
    • (2004) Injury Prevention , vol.10 , pp. 186-191
    • Clark, D.1
  • 36
    • 0025813195 scopus 로고
    • A Monte Carlo method for Bayesian inference in frailty models
    • Clayton, D. G. (1991) A Monte Carlo method for Bayesian inference in frailty models. Biometrics, 47, 467-485.
    • (1991) Biometrics , vol.47 , pp. 467-485
    • Clayton, D.G.1
  • 38
    • 0035755636 scopus 로고    scopus 로고
    • A comparison of inclusive and restrictive strategies in modern missing data procedures
    • Collins, L. M., Schafer, J. L. and Kam, C. M. (2001) A comparison of inclusive and restrictive strategies in modern missing data procedures. Psychological Methods, 6, 330-351.
    • (2001) Psychological Methods , vol.6 , pp. 330-351
    • Collins, L.M.1    Schafer, J.L.2    Kam, C.M.3
  • 40
    • 0000976601 scopus 로고    scopus 로고
    • Meta-analysis, funnel plots and sensitivity analysis
    • Copas, J. B. and Shi, J. Q. (2000) Meta-analysis, funnel plots and sensitivity analysis. Biostatistics, 1, 247-262.
    • (2000) Biostatistics , vol.1 , pp. 247-262
    • Copas, J.B.1    Shi, J.Q.2
  • 41
    • 21344474305 scopus 로고    scopus 로고
    • Accelerating Monte Carlo Markov chain convergence for cumulative-link generalized linear models
    • Cowles, M. K. (1996) Accelerating Monte Carlo Markov chain convergence for cumulative-link generalized linear models. Statistics and Computing, 6, 101-110.
    • (1996) Statistics and Computing , vol.6 , pp. 101-110
    • Cowles, M.K.1
  • 42
    • 84949757230 scopus 로고    scopus 로고
    • Documentation of the Youth Cohort Time-Series Datasets, UK Data Archive Study Number 5765, Economic and Social Data Service
    • Croxford, L., Ianelli, C. and Shapira, M. (2007) Documentation of the Youth Cohort Time-Series Datasets, UK Data Archive Study Number 5765, Economic and Social Data Service.
    • (2007)
    • Croxford, L.1    Ianelli, C.2    Shapira, M.3
  • 43
  • 45
    • 0033636008 scopus 로고    scopus 로고
    • Reparameterizing the pattern mixture model for sensitivity analysis under informative dropout
    • Daniels, M. J. and Hogan, J. W. (2000) Reparameterizing the pattern mixture model for sensitivity analysis under informative dropout. Biometrics, 56, 1241-1248.
    • (2000) Biometrics , vol.56 , pp. 1241-1248
    • Daniels, M.J.1    Hogan, J.W.2
  • 47
    • 0042066687 scopus 로고    scopus 로고
    • On the performance of random coefficient pattern mixture models for non-ignorable dropout
    • Demirtas, H. and Schafer, J. L. (2003) On the performance of random coefficient pattern mixture models for non-ignorable dropout. Statistics in Medicine, 22, 2553-2575.
    • (2003) Statistics in Medicine , vol.22 , pp. 2553-2575
    • Demirtas, H.1    Schafer, J.L.2
  • 48
    • 38349186156 scopus 로고    scopus 로고
    • Plausibility of multivariate normality assumption when multiply imputing non-Gaussain continuous outcomes: a simulation assessment
    • Demirtas, H., Freels, S. A. and Yucel, R. M. (2008) Plausibility of multivariate normality assumption when multiply imputing non-Gaussain continuous outcomes: a simulation assessment. Journal of Statistical Computation and Simulation, 78, 69-84.
    • (2008) Journal of Statistical Computation and Simulation , vol.78 , pp. 69-84
    • Demirtas, H.1    Freels, S.A.2    Yucel, R.M.3
  • 51
    • 79951945425 scopus 로고    scopus 로고
    • Multiple imputation in practice: a case study using a complex German establishment survey
    • Drechsler, J. (2011) Multiple imputation in practice: a case study using a complex German establishment survey. Advances in Statistical Analysis, 95, 1-26.
    • (2011) Advances in Statistical Analysis , vol.95 , pp. 1-26
    • Drechsler, J.1
  • 54
    • 0002178053 scopus 로고
    • Bias reduction of maximum likelihood estimates
    • Firth, D. (1993) Bias reduction of maximum likelihood estimates. Biometrika, 80, 27-38.
    • (1993) Biometrika , vol.80 , pp. 27-38
    • Firth, D.1
  • 56
    • 0000954353 scopus 로고    scopus 로고
    • Efficient Metropolis jumping rules
    • Eds J. M. Bernardo, J. O. Berger, A. F. Dawid and A. F. M. Smith, Oxford: Oxford University Press
    • Gelman, A. G., Roberts, G. O. and Gilks, W. R. (1996) Efficient Metropolis jumping rules. In Bayesian Statistics V (Eds J. M. Bernardo, J. O. Berger, A. F. Dawid and A. F. M. Smith), pp. 599-608. Oxford: Oxford University Press.
    • (1996) Bayesian Statistics V , pp. 599-608
    • Gelman, A.G.1    Roberts, G.O.2    Gilks, W.R.3
  • 60
  • 62
    • 84949884465 scopus 로고    scopus 로고
    • Fitting multilevel multivariate models with missing data in responses and covariates, which may include interactions and non-linear terms
    • Goldstein, H., Carpenter, J. R. and Browne, W. (2012a) Fitting multilevel multivariate models with missing data in responses and covariates, which may include interactions and non-linear terms. Submitted.
    • (2012) Submitted
    • Goldstein, H.1    Carpenter, J.R.2    Browne, W.3
  • 63
    • 84870248573 scopus 로고    scopus 로고
    • The analysis of record-linked data using multiple imputation with data value priors
    • Goldstein, H., Harron, K. and Wade, A. (2012b) The analysis of record-linked data using multiple imputation with data value priors. Statistics in Medicine doi:10.1002/sim.5508.
    • (2012) Statistics in Medicine
    • Goldstein, H.1    Harron, K.2    Wade, A.3
  • 65
    • 33645617067 scopus 로고    scopus 로고
    • Ph.D. thesis, Department of Statistics, The Pennsylvania State University, University Park, PA
    • Harel, O. (2003) Strategies for data analysis with two types of missing values. Ph.D. thesis, Department of Statistics, The Pennsylvania State University, University Park, PA.
    • (2003) Strategies for data analysis with two types of missing values
    • Harel, O.1
  • 66
    • 33845210459 scopus 로고    scopus 로고
    • Inferences on missing information under multiple imputation and twostage multiple imputation
    • Harel, O. (2007) Inferences on missing information under multiple imputation and twostage multiple imputation. Statistical Methodology, 4, 75-79.
    • (2007) Statistical Methodology , vol.4 , pp. 75-79
    • Harel, O.1
  • 68
    • 84949884466 scopus 로고    scopus 로고
    • Complete records regression with missing data:relating bias in coefficient estimates to the missingness mechanism
    • in preparation
    • Harel, O. and Carpenter, J. R. (2012) Complete records regression with missing data:relating bias in coefficient estimates to the missingness mechanism, in preparation.
    • (2012)
    • Harel, O.1    Carpenter, J.R.2
  • 70
    • 60449120489 scopus 로고    scopus 로고
    • Partial and latent ignorability in missing data problems
    • Harel, O. and Schafer, J. L. (2009) Partial and latent ignorability in missing data problems. Biometrika, 96, 37-50.
    • (2009) Biometrika , vol.96 , pp. 37-50
    • Harel, O.1    Schafer, J.L.2
  • 72
    • 0000620901 scopus 로고
    • Missing values in experiments analyzed on automatic computers
    • Healy, M. J. R. and Westmacott, M. (1956) Missing values in experiments analyzed on automatic computers. Applied Statistics, 5, 203-206.
    • (1956) Applied Statistics , vol.5 , pp. 203-206
    • Healy, M.J.R.1    Westmacott, M.2
  • 73
    • 84949761177 scopus 로고    scopus 로고
    • Missing outcome data in meta-analysis of clinical trials: development and comparison of methods, with recommendations for practice
    • Higgins, J. P. T., White, I. R. and Wood, A. (2006) Missing outcome data in meta-analysis of clinical trials: development and comparison of methods, with recommendations for practice. Technical report, MRC Biostatistcs Unit, Cambridge UK.
    • (2006) Technical report, MRC Biostatistcs Unit, Cambridge UK
    • Higgins, J.P.T.1    White, I.R.2    Wood, A.3
  • 74
    • 34447619161 scopus 로고    scopus 로고
    • Derivation and validation of QRISK, a new cardiovascular disease risk score for the United Kingdom: prospective open cohort study
    • Hippisley-Cox, J., Coupland, C., Vinogradova, Y., Robson, J., May, M. and Brindle, P. (2007) Derivation and validation of QRISK, a new cardiovascular disease risk score for the United Kingdom: prospective open cohort study. British Medical Journal, 335, 7611-7623.
    • (2007) British Medical Journal , vol.335 , pp. 7611-7623
    • Hippisley-Cox, J.1    Coupland, C.2    Vinogradova, Y.3    Robson, J.4    May, M.5    Brindle, P.6
  • 75
    • 0033906922 scopus 로고
    • Ridge regression: biased estimation for nonorthogonal problems
    • Hoerl, A. E. and Kennard, R. W. (1970) Ridge regression: biased estimation for nonorthogonal problems. Technometrics, 42, 80-86.
    • (1970) Technometrics , vol.42 , pp. 80-86
    • Hoerl, A.E.1    Kennard, R.W.2
  • 76
    • 0033546995 scopus 로고    scopus 로고
    • What is meant by intention to treat analysis? Survey of published randomised controlled trials
    • Hollis, S. and Campbell, F. (1999) What is meant by intention to treat analysis? Survey of published randomised controlled trials. British Medical Journal, 319, 670-674.
    • (1999) British Medical Journal , vol.319 , pp. 670-674
    • Hollis, S.1    Campbell, F.2
  • 78
    • 0242710940 scopus 로고    scopus 로고
    • A potential for bias when rounding in multiple imputation
    • Horton, N. J., Lipsitz, S. R. and Parzen, M. (2003) A potential for bias when rounding in multiple imputation. The American Statistician, 57, 229-232.
    • (2003) The American Statistician , vol.57 , pp. 229-232
    • Horton, N.J.1    Lipsitz, S.R.2    Parzen, M.3
  • 80
    • 33750063475 scopus 로고    scopus 로고
    • Survival analysis using auxiliary variables via nonparametric multiple imputation
    • Hsu, C.-H., Taylor, J. M. G., Murray, S. and Commenges, D. (2006) Survival analysis using auxiliary variables via nonparametric multiple imputation. Statistics in Medicine, 25, 3503-3517.
    • (2006) Statistics in Medicine , vol.25 , pp. 3503-3517
    • Hsu, C.-H.1    Taylor, J.M.G.2    Murray, S.3    Commenges, D.4
  • 81
    • 33846820182 scopus 로고    scopus 로고
    • Multiple imputation for interval censored data with auxiliary variables
    • Hsu, C.-H., Taylor, J. M. G., Murray, S. and Commenges, D. (2007) Multiple imputation for interval censored data with auxiliary variables. Statistics in Medicine, 26, 769-781.
    • (2007) Statistics in Medicine , vol.26 , pp. 769-781
    • Hsu, C.-H.1    Taylor, J.M.G.2    Murray, S.3    Commenges, D.4
  • 82
    • 63049126380 scopus 로고    scopus 로고
    • Nonparametric comparison of two survival functions with dependent censoring via nonparametric multiple imputation
    • Hsu, C.-H., and Taylor, J. M. G. (2009) Nonparametric comparison of two survival functions with dependent censoring via nonparametric multiple imputation. Statistics in Medicine, 28, 462-475.
    • (2009) Statistics in Medicine , vol.28 , pp. 462-475
    • Hsu, C.-H.1    Taylor, J.M.G.2
  • 83
    • 84949884467 scopus 로고    scopus 로고
    • Joint modelling rationale for chained equations imputation
    • University of Bristol, Department of Social Medicine
    • Hughes, R., White, I. R., Carpenter, J. R., Tilling, K. and Sterne, J. A. C. (2012a) Joint modelling rationale for chained equations imputation. Technical report, University of Bristol, Department of Social Medicine.
    • (2012) Technical report
    • Hughes, R.1    White, I.R.2    Carpenter, J.R.3    Tilling, K.4    Sterne, J.A.C.5
  • 84
    • 84949884468 scopus 로고    scopus 로고
    • Comparison of imputation variance estimators
    • University of Bristol, Department of Social Medicine
    • Hughes, R. A., Sterne, J. A. C. and Tilling, K. (2012b) Comparison of imputation variance estimators. Technical report, University of Bristol, Department of Social Medicine.
    • (2012) Technical report
    • Hughes, R.A.1    Sterne, J.A.C.2    Tilling, K.3
  • 85
    • 0028950887 scopus 로고
    • Probabilistic linkage of large public health data files
    • Jaro, M. (1995) Probabilistic linkage of large public health data files. Statistics in Medicine, 14, 491-498.
    • (1995) Statistics in Medicine , vol.14 , pp. 491-498
    • Jaro, M.1
  • 86
    • 46249131752 scopus 로고    scopus 로고
    • Demystifying double robustness: A comparison of alternative strategies for estimating a population mean from incomplete data (with discussion)
    • Kang, J. D. Y. and Schafer, J. L. (2007) Demystifying double robustness: A comparison of alternative strategies for estimating a population mean from incomplete data (with discussion). Statistical Science, 22, 523-539.
    • (2007) Statistical Science , vol.22 , pp. 523-539
    • Kang, J.D.Y.1    Schafer, J.L.2
  • 87
    • 0032534724 scopus 로고    scopus 로고
    • Selection models for repeated measurements with non-random dropout: an illustration of sensitivity
    • Kenward, M. G. (1998) Selection models for repeated measurements with non-random dropout: an illustration of sensitivity. Statistics in Medicine, 17, 2723-2732.
    • (1998) Statistics in Medicine , vol.17 , pp. 2723-2732
    • Kenward, M.G.1
  • 89
    • 84872156540 scopus 로고    scopus 로고
    • Multiple imputation
    • Eds M. Davidian, G. Fitzmaurice, G. Molenberghs and G. Verbeke, London: Chapman & Hall/CRC
    • Kenward, M. G. and Carpenter, J. R. (2009) Multiple imputation. In Longitudinal Data Analysis: A Handbook of Modern Statistical Methods (Eds M. Davidian, G. Fitzmaurice, G. Molenberghs and G. Verbeke), pp. 477-500. London: Chapman & Hall/CRC.
    • (2009) Longitudinal Data Analysis: A Handbook of Modern Statistical Methods , pp. 477-500
    • Kenward, M.G.1    Carpenter, J.R.2
  • 90
    • 0345734935 scopus 로고    scopus 로고
    • Likelihood based frequentist inference when data are missing at random
    • Kenward, M. G. and Molenberghs, G. (1998) Likelihood based frequentist inference when data are missing at random. Statistical Science, 13, 236-247.
    • (1998) Statistical Science , vol.13 , pp. 236-247
    • Kenward, M.G.1    Molenberghs, G.2
  • 92
    • 1542341537 scopus 로고    scopus 로고
    • Pattern-mixture models with proper time dependence
    • Kenward, M. G., Molenberghs, G. and Thijs, H. (2003) Pattern-mixture models with proper time dependence. Biometrika, 90, 53-71.
    • (2003) Biometrika , vol.90 , pp. 53-71
    • Kenward, M.G.1    Molenberghs, G.2    Thijs, H.3
  • 93
    • 24344487552 scopus 로고    scopus 로고
    • A note on approximate Bayesian boostrap imputation
    • Kim, J. K. (2002) A note on approximate Bayesian boostrap imputation. Biometrika, 89, 470-477.
    • (2002) Biometrika , vol.89 , pp. 470-477
    • Kim, J.K.1
  • 95
    • 49449091081 scopus 로고    scopus 로고
    • Use of multiple imputation in the epidemiologic literature
    • Klebanoff, M. A. and Cole, S. R. (2008) Use of multiple imputation in the epidemiologic literature. American Journal of Epidemiology, 168, 355-357.
    • (2008) American Journal of Epidemiology , vol.168 , pp. 355-357
    • Klebanoff, M.A.1    Cole, S.R.2
  • 97
    • 0029157096 scopus 로고
    • A multiple imputation strategy for clinical trials with trunction of patient data
    • Lavori, P. W., Dawson, R. and Shera, D. (1995) A multiple imputation strategy for clinical trials with trunction of patient data. Statistics in Medicine, 14, 1913-1925.
    • (1995) Statistics in Medicine , vol.14 , pp. 1913-1925
    • Lavori, P.W.1    Dawson, R.2    Shera, D.3
  • 98
    • 77249147857 scopus 로고    scopus 로고
    • Multiple imputation for missing data: fully conditional specification versus multivariate normal imputation
    • Lee, K. J. and Carlin, J. B. (2010) Multiple imputation for missing data: fully conditional specification versus multivariate normal imputation. American Journal of Epidemiology, 171, 624-632.
    • (2010) American Journal of Epidemiology , vol.171 , pp. 624-632
    • Lee, K.J.1    Carlin, J.B.2
  • 99
    • 0000265107 scopus 로고
    • Large-sample significance levels from multiply-imputed data using moment-based statistics and an F reference distribution
    • Li, K. H., Raghunathan, T. E. and Rubin, D. B. (1991) Large-sample significance levels from multiply-imputed data using moment-based statistics and an F reference distribution. Journal of the American Statistical Association, 86, 1065-1073.
    • (1991) Journal of the American Statistical Association , vol.86 , pp. 1065-1073
    • Li, K.H.1    Raghunathan, T.E.2    Rubin, D.B.3
  • 100
  • 101
    • 77956890002 scopus 로고
    • A class of pattern-mixture models for multivariate incomplete data
    • Little, R. J. A. (1994) A class of pattern-mixture models for multivariate incomplete data. Biometrika, 81, 471-483.
    • (1994) Biometrika , vol.81 , pp. 471-483
    • Little, R.J.A.1
  • 104
    • 0030460385 scopus 로고    scopus 로고
    • Intent-to-treat analysis for longitudinal studies with dropouts
    • Little, R. J. A. and Yau, L. (1996) Intent-to-treat analysis for longitudinal studies with dropouts. Biometrics, 52, 471-483.
    • (1996) Biometrics , vol.52 , pp. 471-483
    • Little, R.J.A.1    Yau, L.2
  • 106
    • 0010657302 scopus 로고
    • Bayesian statistical inference for sampling from a finite population
    • Lo, A. Y. (1986) Bayesian statistical inference for sampling from a finite population. Annals of Statistics, 14, 1226-1233.
    • (1986) Annals of Statistics , vol.14 , pp. 1226-1233
    • Lo, A.Y.1
  • 108
    • 0037629206 scopus 로고    scopus 로고
    • Simple approaches to assess the possible impact of missing outcome information on estimates of risk ratios, odds ratios, and risk differences
    • Magder, L. S. (2003) Simple approaches to assess the possible impact of missing outcome information on estimates of risk ratios, odds ratios, and risk differences. Controlled Clinical Trials, 24.
    • (2003) Controlled Clinical Trials , pp. 24
    • Magder, L.S.1
  • 111
    • 84972537494 scopus 로고
    • Multiple-imputation inferences with uncongenial sources of input (with discussion)
    • Meng, X. L. (1994) Multiple-imputation inferences with uncongenial sources of input (with discussion). Statistical Science, 10, 538-573.
    • (1994) Statistical Science , vol.10 , pp. 538-573
    • Meng, X.L.1
  • 112
    • 0344379018 scopus 로고    scopus 로고
    • Discussion: Efficiency and self-efficiency with multiple imputation inference
    • Meng, X. L. and Romero, M. (2003) Discussion: Efficiency and self-efficiency with multiple imputation inference. International Statistical Review, 71, 607-618.
    • (2003) International Statistical Review , vol.71 , pp. 607-618
    • Meng, X.L.1    Romero, M.2
  • 113
    • 34347391805 scopus 로고
    • Performing likelihood ratio tests with multiplyimputed data sets
    • Meng, X. L. and Rubin, D. B. (1992) Performing likelihood ratio tests with multiplyimputed data sets. Biometrika, 89, 267-278.
    • (1992) Biometrika , vol.89 , pp. 267-278
    • Meng, X.L.1    Rubin, D.B.2
  • 116
    • 84949884469 scopus 로고    scopus 로고
    • Glossary accessed 17 October 2011 at
    • National Institute for Clinical Excellence (NICE) (2011) Glossary accessed 17 October 2011 at http://www.nice.org.uk/website/glossary/glossary.jsp.
    • (2011)
  • 117
    • 79952576381 scopus 로고    scopus 로고
    • Panel on Handling Missing Data in Clinical Trials. Committee on National Statistics, Division of Behavioral and Social Sciences and Education. Washington, DC:The National Academies Press
    • National Research Council (2010) The Prevention and Treatment of Missing Data in Clinical Trials. Panel on Handling Missing Data in Clinical Trials. Committee on National Statistics, Division of Behavioral and Social Sciences and Education. Washington, DC:The National Academies Press.
    • (2010) The Prevention and Treatment of Missing Data in Clinical Trials
  • 118
    • 72849117782 scopus 로고    scopus 로고
    • Missing values in longitudinal dietary data: a multiple imputation approach based on a fully conditional specification
    • Nevalainen, J., Kenward, M. G. and Virtanen, S. M. (2009) Missing values in longitudinal dietary data: a multiple imputation approach based on a fully conditional specification. Statistics in Medicine, 28, 3657-3669.
    • (2009) Statistics in Medicine , vol.28 , pp. 3657-3669
    • Nevalainen, J.1    Kenward, M.G.2    Virtanen, S.M.3
  • 119
    • 0345659236 scopus 로고    scopus 로고
    • Proper and improper multiple imputation
    • Nielsen, S. F. (2003) Proper and improper multiple imputation. International Statistical Review, 71, 593-627.
    • (2003) International Statistical Review , vol.71 , pp. 593-627
    • Nielsen, S.F.1
  • 121
    • 0000317187 scopus 로고
    • Multivariate correlation models with mixed discrete and continuous variables
    • Olkin, I. and Tate, R. F. (1961) Multivariate correlation models with mixed discrete and continuous variables. Annals of Mathematical Statistics, 32, 448-465.
    • (1961) Annals of Mathematical Statistics , vol.32 , pp. 448-465
    • Olkin, I.1    Tate, R.F.2
  • 124
    • 29344444069 scopus 로고    scopus 로고
    • National Child Development Study and 1970 British Cohort Study Technical Report: Changes in the NCDS and BCS70 populations and samples over time
    • London: Institute of Education, University of London
    • Plewis, I., Calderwood, L., Hawkes, D. and Nathan, G. (2004) National Child Development Study and 1970 British Cohort Study Technical Report: Changes in the NCDS and BCS70 populations and samples over time. London: Institute of Education, University of London.
    • (2004)
    • Plewis, I.1    Calderwood, L.2    Hawkes, D.3    Nathan, G.4
  • 125
    • 33845369981 scopus 로고    scopus 로고
    • Combining information from multiple surveys for assessing health disparities
    • Raghunathan, T. E. (2006) Combining information from multiple surveys for assessing health disparities. Allgemeines Statistisches Archiv, 90, 515-526.
    • (2006) Allgemeines Statistisches Archiv , vol.90 , pp. 515-526
    • Raghunathan, T.E.1
  • 126
    • 0002344593 scopus 로고    scopus 로고
    • A multivariate technique for multiply imputing missing values using a sequence of regression models
    • Raghunathan, T. E., Lepkowski, J. M., Van Hoewyk, J. and Solenberger, P. (2001) A multivariate technique for multiply imputing missing values using a sequence of regression models. Survey Methodology, 27, 85-95.
    • (2001) Survey Methodology , vol.27 , pp. 85-95
    • Raghunathan, T.E.1    Lepkowski, J.M.2    Van Hoewyk, J.3    Solenberger, P.4
  • 127
    • 0000974584 scopus 로고
    • Jackknife variance estimation with survey data under hot-deck imputation
    • Rao, J. N. K. and Shao, J. (1992) Jackknife variance estimation with survey data under hot-deck imputation. Biometrika, 79, 811-822.
    • (1992) Biometrika , vol.79 , pp. 811-822
    • Rao, J.N.K.1    Shao, J.2
  • 129
    • 34548452163 scopus 로고    scopus 로고
    • Small-sample degrees of freedom for multi-component significance tests with multiple imputation for missing data
    • Reiter, J. P. (2007) Small-sample degrees of freedom for multi-component significance tests with multiple imputation for missing data. Biometrika, 92, 502-508.
    • (2007) Biometrika , vol.92 , pp. 502-508
    • Reiter, J.P.1
  • 132
    • 0031014353 scopus 로고    scopus 로고
    • Non-response models for the analysis of non-monotone ignorable missing data
    • Robins, J. M. and Gill, R. (1997) Non-response models for the analysis of non-monotone ignorable missing data. Statistics in Medicine, 16, 39-56.
    • (1997) Statistics in Medicine , vol.16 , pp. 39-56
    • Robins, J.M.1    Gill, R.2
  • 133
    • 0000555875 scopus 로고    scopus 로고
    • Inference for imputation estimators
    • Robins, J. M. and Wang, N. (2000) Inference for imputation estimators. Biometrika, 85, 113-124.
    • (2000) Biometrika , vol.85 , pp. 113-124
    • Robins, J.M.1    Wang, N.2
  • 134
    • 0026708512 scopus 로고
    • Estimating exposure effects by modelling the expectation of exposure conditional on confounders
    • Robins, J. M., Mark, S. D. and Newey, W. K. (1992) Estimating exposure effects by modelling the expectation of exposure conditional on confounders. Biometrics, 48, 479-495.
    • (1992) Biometrics , vol.48 , pp. 479-495
    • Robins, J.M.1    Mark, S.D.2    Newey, W.K.3
  • 136
    • 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
  • 137
    • 77951622706 scopus 로고
    • The central role of the propensity score in observational studies for causal effects
    • Rosenbaum, P. R. and Rubin, D. B. (1983) The central role of the propensity score in observational studies for causal effects. Biometrika, 70, 41-55.
    • (1983) Biometrika , vol.70 , pp. 41-55
    • Rosenbaum, P.R.1    Rubin, D.B.2
  • 138
    • 84949884470 scopus 로고
    • The model based (prediction) approach to finite population sampling theory
    • Eds M. Ghosh and P. K. Patahak, Institute of Mathematical Statistics
    • Royall, R. M. (1992) The model based (prediction) approach to finite population sampling theory. In Current Issues in Statistial Inference: Essays in Honor of D Basu (Eds M. Ghosh and P. K. Patahak), pp. 225-240. Institute of Mathematical Statistics.
    • (1992) Current Issues in Statistial Inference: Essays in Honor of D Basu , pp. 225-240
    • Royall, R.M.1
  • 139
    • 43749105785 scopus 로고    scopus 로고
    • Multiple imputation of missing values: further update of ice with emphasis on interval censoring
    • Royston, P. (2007) Multiple imputation of missing values: further update of ice with emphasis on interval censoring. The Stata Journal, 7, 445-464.
    • (2007) The Stata Journal , vol.7 , pp. 445-464
    • Royston, P.1
  • 141
    • 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
  • 142
    • 0000135972 scopus 로고
    • The Bayesian bootstrap
    • Rubin, D. B. (1981) The Bayesian bootstrap. Annals of Statistics, 9, 130-134.
    • (1981) Annals of Statistics , vol.9 , pp. 130-134
    • Rubin, D.B.1
  • 145
    • 27644493802 scopus 로고    scopus 로고
    • Discussion on multiple imputation
    • Rubin, D. B. (2003) Discussion on multiple imputation. International Statistical Review, 71, 619-625.
    • (2003) International Statistical Review , vol.71 , pp. 619-625
    • Rubin, D.B.1
  • 146
    • 84950918760 scopus 로고
    • Multiple imputation for interval estimation from simple random samples with ignorable nonresponse
    • Rubin, D. B. and Schenker, N. (1986) Multiple imputation for interval estimation from simple random samples with ignorable nonresponse. Journal of the American Statistical Association, 81, 366-374.
    • (1986) Journal of the American Statistical Association , vol.81 , pp. 366-374
    • Rubin, D.B.1    Schenker, N.2
  • 149
    • 84949884471 scopus 로고    scopus 로고
    • MIX software for multiple imputation of a mix of categorical and continuous data in S+
    • accessed 27 July 2011
    • Schafer, J. L. (1999a) MIX software for multiple imputation of a mix of categorical and continuous data in S+. http://www.stat.psu.edu/jls/misoftwa.html, accessed 27 July 2011.
    • (1999)
    • Schafer, J.L.1
  • 151
  • 152
    • 84949754586 scopus 로고    scopus 로고
    • Increased brain atrophy rates in cognitively normal adults with lower cerebrosphinal fluid Aβ1-42
    • Schott, J. M., Abartlett, J. W., Fox, N. C. and Barnes, J. for the Alzheimer's Disease Neuroimaging Initiative Investigators (2010) Increased brain atrophy rates in cognitively normal adults with lower cerebrosphinal fluid Aβ1-42. Annals of Neurology, 31, 1452-1462.
    • (2010) Annals of Neurology , vol.31 , pp. 1452-1462
    • Schott, J.M.1    Abartlett, J.W.2    Fox, N.C.3    Barnes, J.4
  • 154
    • 84867917862 scopus 로고    scopus 로고
    • Multiple imputation of missing covariates with non-linear effects and interactions: evaluation of statistical methods
    • Seaman, S. R., Bartlett, J. W. and White, I. R. (2012a) Multiple imputation of missing covariates with non-linear effects and interactions: evaluation of statistical methods. BMC Methodology, 12, 46.
    • (2012) BMC Methodology , vol.12 , pp. 46
    • Seaman, S.R.1    Bartlett, J.W.2    White, I.R.3
  • 155
    • 84858861527 scopus 로고    scopus 로고
    • Combining multiple imputation and inverse-probability weighting
    • Seaman, S. R., White, I. R., Copas, A. J. and Li, L. (2012b) Combining multiple imputation and inverse-probability weighting. Biometrics, 68, 129-137.
    • (2012) Biometrics , vol.68 , pp. 129-137
    • Seaman, S.R.1    White, I.R.2    Copas, A.J.3    Li, L.4
  • 156
    • 0010342144 scopus 로고    scopus 로고
    • Ph.D. thesis, Department of Statistics, Harvard University, Cambridge, MA
    • Shen, Z. J. (2000) Nested multiple imputation. Ph.D. thesis, Department of Statistics, Harvard University, Cambridge, MA.
    • (2000) Nested multiple imputation
    • Shen, Z.J.1
  • 157
    • 55549128556 scopus 로고    scopus 로고
    • Using an approximate Bayesian bootstrap to multiply impute nonignorable missing data
    • Siddique, J. and Belin, T. R. (2008) Using an approximate Bayesian bootstrap to multiply impute nonignorable missing data. Computational Statistics and Data Analysis, 53, 405-415.
    • (2008) Computational Statistics and Data Analysis , vol.53 , pp. 405-415
    • Siddique, J.1    Belin, T.R.2
  • 159
    • 0442293940 scopus 로고    scopus 로고
    • Estimation and inference for logistic regression with covariate misclassification and measurement error, in main study/ validation study designs
    • Spiegelman, D., Rosner, B. and Logan, R. (2000) Estimation and inference for logistic regression with covariate misclassification and measurement error, in main study/ validation study designs. Journal of the American Statistical Association, 95, 51-61.
    • (2000) Journal of the American Statistical Association , vol.95 , pp. 51-61
    • Spiegelman, D.1    Rosner, B.2    Logan, R.3
  • 160
    • 84993742006 scopus 로고    scopus 로고
    • A general multilevel multistate competing risks model for event history data, with an application to a study of contraceptive use dynamics
    • Steele, F., Goldstein, H. and Browne, W. (2004) A general multilevel multistate competing risks model for event history data, with an application to a study of contraceptive use dynamics. Statistical Modelling, 4, 145-159.
    • (2004) Statistical Modelling , vol.4 , pp. 145-159
    • Steele, F.1    Goldstein, H.2    Browne, W.3
  • 162
    • 84863414529 scopus 로고    scopus 로고
    • Multiple imputation with diagnostics (mi) in R: opening windows into the black box
    • Su, Y., Gelmand, A., Hill, J. and Yajima, M. (2011) Multiple imputation with diagnostics (mi) in R: opening windows into the black box. Journal of Statistical Software, 45, 1-31.
    • (2011) Journal of Statistical Software , vol.45 , pp. 1-31
    • Su, Y.1    Gelmand, A.2    Hill, J.3    Yajima, M.4
  • 163
    • 77955858058 scopus 로고    scopus 로고
    • Bounded, efficient and doubly robust estimation with inverse weighting
    • Tan, Z. (2010) Bounded, efficient and doubly robust estimation with inverse weighting. Biometrics, 97, 661-682.
    • (2010) Biometrics , vol.97 , pp. 661-682
    • Tan, Z.1
  • 164
    • 84950758368 scopus 로고
    • The calculation of posterior distributions by Data Augmentation (with discussion)
    • Tanner, M. and Wong, W. (1987) The calculation of posterior distributions by Data Augmentation (with discussion). Journal of the American Statistical Association, 82, 528-550.
    • (1987) Journal of the American Statistical Association , vol.82 , pp. 528-550
    • Tanner, M.1    Wong, W.2
  • 170
    • 79959330030 scopus 로고    scopus 로고
    • Improved doubly robust estimation when data are monotonely coarsened, with application to longitudinal studies with dropout
    • Tsiatis, A. A., Davidian, M. and Cao, W. (2011) Improved doubly robust estimation when data are monotonely coarsened, with application to longitudinal studies with dropout. Biometrics, 67, 536-545.
    • (2011) Biometrics , vol.67 , pp. 536-545
    • Tsiatis, A.A.1    Davidian, M.2    Cao, W.3
  • 171
    • 34347407592 scopus 로고    scopus 로고
    • Youth Cohort Time Series for England, Wales and Scotland, 1984-2002 (computer file SN 5765). First Edition, Colchester, Essex: UK Data Archive, November 2007. van Buuren, S. (2007) Multiple imputation of discrete and continuous data by fully conditional specification
    • UK Data Archive (2007) Youth Cohort Time Series for England, Wales and Scotland, 1984-2002 (computer file SN 5765). First Edition, Colchester, Essex: UK Data Archive, November 2007. van Buuren, S. (2007) Multiple imputation of discrete and continuous data by fully conditional specification. Statistical Methods in Medical Research, 16, 219-242.
    • (2007) Statistical Methods in Medical Research , vol.16 , pp. 219-242
  • 172
    • 0033616909 scopus 로고    scopus 로고
    • Multiple imputation of missing blood presure covariates in survival analysis
    • van Buuren, S., Boshuizen, H. C. and Knook, D. L. (1999) Multiple imputation of missing blood presure covariates in survival analysis. Statistics in Medicine, 18, 681-694.
    • (1999) Statistics in Medicine , vol.18 , pp. 681-694
    • Van Buuren, S.1    Boshuizen, H.C.2    Knook, D.L.3
  • 173
    • 37549032131 scopus 로고    scopus 로고
    • Estimation of regression models for the mean of repeated outcomes under nonignorable nonmonotone nonresponse
    • Vansteelandt, S., Rotnitzky, A. and Robins, J. M. (2007) Estimation of regression models for the mean of repeated outcomes under nonignorable nonmonotone nonresponse. Biometrika, 94, 841-860.
    • (2007) Biometrika , vol.94 , pp. 841-860
    • Vansteelandt, S.1    Rotnitzky, A.2    Robins, J.M.3
  • 177
    • 0036732922 scopus 로고    scopus 로고
    • A Monte Carlo EM algorithm for random coefficient-based dropout models
    • Verzilli, C. and Carpenter, J. R. (2002) A Monte Carlo EM algorithm for random coefficient-based dropout models. Journal of Applied Statistics, 29, 1011-1021.
    • (2002) Journal of Applied Statistics , vol.29 , pp. 1011-1021
    • Verzilli, C.1    Carpenter, J.R.2
  • 178
    • 69149105188 scopus 로고    scopus 로고
    • How to impute interactions, squares and other transformed variables
    • Von Hippel, P. T. (2009) How to impute interactions, squares and other transformed variables. Sociological Methodology, 39, 265-291.
    • (2009) Sociological Methodology , vol.39 , pp. 265-291
    • Von Hippel, P.T.1
  • 179
    • 84949760499 scopus 로고    scopus 로고
    • Improving medical records: examining factors associated with better documentation of paediatric admissions to eight Kenyan hospitals enrolled in a cluster randomised trial
    • In preparation
    • Wagai, J., Ntoburi, S., Irimu, G., Opiyo, N., Ayieko, P., Opondo, C., Carpenter, J. R. and English, M. (2012) Improving medical records: examining factors associated with better documentation of paediatric admissions to eight Kenyan hospitals enrolled in a cluster randomised trial. In preparation.
    • (2012)
    • Wagai, J.1    Ntoburi, S.2    Irimu, G.3    Opiyo, N.4    Ayieko, P.5    Opondo, C.6    Carpenter, J.R.7    English, M.8
  • 180
    • 0011936489 scopus 로고    scopus 로고
    • Large-sample theory for parametric multiple imputation procedures
    • Wang, N. and Robins, J. M. (1998) Large-sample theory for parametric multiple imputation procedures. Biometrika, 85, 935-948.
    • (1998) Biometrika , vol.85 , pp. 935-948
    • Wang, N.1    Robins, J.M.2
  • 181
    • 84949884473 scopus 로고    scopus 로고
    • Multiple imputation for general practice records: application of 'forwards-backwards' algorithm
    • Forthcoming
    • Welch, C., Petersen, I. and Carpenter, J. R. (2012) Multiple imputation for general practice records: application of 'forwards-backwards' algorithm. Forthcoming.
    • (2012)
    • Welch, C.1    Petersen, I.2    Carpenter, J.R.3
  • 182
    • 85035260839 scopus 로고    scopus 로고
    • Smoothing spline models for longitudinal data
    • Eds M. Davidian, G. Fitzmaurice, G. Molenberghs and G. Verbeke, Chichester: John Wiley & Sons, Ltd
    • Welham, S. (2010) Smoothing spline models for longitudinal data. In Longitudinal Data Analysis: A Handbook of Modern Statistical Methods (Eds M. Davidian, G. Fitzmaurice, G. Molenberghs and G. Verbeke), pp. 253-290. Chichester: John Wiley & Sons, Ltd.
    • (2010) Longitudinal Data Analysis: A Handbook of Modern Statistical Methods , pp. 253-290
    • Welham, S.1
  • 183
    • 34249281320 scopus 로고    scopus 로고
    • Eliciting and using expert opinions about non-response bias in randomised controlled trials
    • White, I., Carpenter, J. R., Evans, S. and Schroter, S. (2007) Eliciting and using expert opinions about non-response bias in randomised controlled trials. Clinical Trials, 4, 125-139.
    • (2007) Clinical Trials , vol.4 , pp. 125-139
    • White, I.1    Carpenter, J.R.2    Evans, S.3    Schroter, S.4
  • 184
    • 33749602419 scopus 로고    scopus 로고
    • Commentary: dealing with measurement error: multiple imputation or regression calibration
    • White, I. R. (2006) Commentary: dealing with measurement error: multiple imputation or regression calibration. International Journal of Edpidemiology, 35, 1081-1082.
    • (2006) International Journal of Edpidemiology , vol.35 , pp. 1081-1082
    • White, I.R.1
  • 185
    • 69949108828 scopus 로고    scopus 로고
    • Imputing missing covariate values for the Cox model
    • White, I. R. and Royston, P. (2009) Imputing missing covariate values for the Cox model. Statistics in Medicine, 28, 1982-1998.
    • (2009) Statistics in Medicine , vol.28 , pp. 1982-1998
    • White, I.R.1    Royston, P.2
  • 186
    • 77955271783 scopus 로고    scopus 로고
    • Avoiding bias due to perfect prediction in multiple imputation of incompete categorical variables
    • White, I. R., Daniel, R. and Royston, P. (2010) Avoiding bias due to perfect prediction in multiple imputation of incompete categorical variables. Computational Statistics and Data Analysis, 54, 2267-2275.
    • (2010) Computational Statistics and Data Analysis , vol.54 , pp. 2267-2275
    • White, I.R.1    Daniel, R.2    Royston, P.3
  • 187
    • 84949884475 scopus 로고    scopus 로고
    • Strategies for multiple imputation in individual patient data meta-analysis
    • Wood, A., Burgess, S. and White, I. R. (2012) Strategies for multiple imputation in individual patient data meta-analysis. Submitted for publication.
    • (2012) Submitted for publication
    • Wood, A.1    Burgess, S.2    White, I.R.3
  • 188
  • 189
    • 80051757583 scopus 로고    scopus 로고
    • Random covariances and mixed-effects models for imputing multivariate multilevel continuous data
    • Yucel, R. M. (2011) Random covariances and mixed-effects models for imputing multivariate multilevel continuous data. Statistical Modelling, 11, 351-370.
    • (2011) Statistical Modelling , vol.11 , pp. 351-370
    • Yucel, R.M.1
  • 190
    • 29144531339 scopus 로고    scopus 로고
    • Imputation of binary treatment variables with measurement error in administrative data
    • Yucel, R. M. and Zaslavsky, A. M. (2005) Imputation of binary treatment variables with measurement error in administrative data. Journal of the American Statistical Association, 100, 1123-1132.
    • (2005) Journal of the American Statistical Association , vol.100 , pp. 1123-1132
    • Yucel, R.M.1    Zaslavsky, A.M.2
  • 191
    • 0344379016 scopus 로고
    • Comment on Meng, X-L., 'Multiple-imputation inferences with uncongenial sources of input'
    • Zaslavsky, A. (1994) Comment on Meng, X-L., 'Multiple-imputation inferences with uncongenial sources of input'. Statistical Science, 9, 563-566.
    • (1994) Statistical Science , vol.9 , pp. 563-566
    • Zaslavsky, A.1


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