메뉴 건너뛰기




Volumn 37, Issue 3, 2010, Pages 489-500

A distance-based rounding strategy for post-imputation ordinal data

Author keywords

Bias; Multiple imputation; Ordinal data; Precision; Rounding

Indexed keywords


EID: 77649115914     PISSN: 02664763     EISSN: 13600532     Source Type: Journal    
DOI: 10.1080/02664760902744954     Document Type: Article
Times cited : (8)

References (26)
  • 1
    • 0033619671 scopus 로고    scopus 로고
    • Performance of a general location model with an ignorable missing data assumption in a multivariate mental health services study
    • T.R. Belin, M.Y. Hu,A.S.Young, and O. Grusky, Performance of a general location model with an ignorable missing data assumption in a multivariate mental health services study, Statist. Med. 18 (1999), pp. 3123-3135.
    • (1999) Statist. Med. , vol.18 , pp. 3123-3135
    • Belin, T.R.1    Hu, M.Y.2    Young, A.S.3    Grusky, O.4
  • 2
    • 0035755636 scopus 로고    scopus 로고
    • A comparison of inclusive and restrictive strategies in modern missing data procedures
    • L.M. Collins, J.L. Schafer, and C.H. Kam, A comparison of inclusive and restrictive strategies in modern missing data procedures, Psychol. Methods 6 (2001), pp. 330-351.
    • (2001) Psychol. Methods , vol.6 , pp. 330-351
    • Collins, L.M.1    Schafer, J.L.2    Kam, C.H.3
  • 3
    • 10944236293 scopus 로고    scopus 로고
    • Simulation-driven inferences for multiply imputed longitudinal datasets
    • H. Demirtas, Simulation-driven inferences for multiply imputed longitudinal datasets, Statist. Neerlandica 58 (2004), pp. 466-482.
    • (2004) Statist. Neerlandica , vol.58 , pp. 466-482
    • Demirtas, H.1
  • 4
    • 18744401063 scopus 로고    scopus 로고
    • Bayesian analysis of hierarchical pattern-mixture models for clinical trials data with attrition and comparisons to commonly used ad-hoc and model-based approaches
    • H. Demirtas, Bayesian analysis of hierarchical pattern-mixture models for clinical trials data with attrition and comparisons to commonly used ad-hoc and model-based approaches, J. Biopharmaceut. Statist. 25 (2005), pp. 383-402.
    • (2005) J. Biopharmaceut. Statist. , vol.25 , pp. 383-402
    • Demirtas, H.1
  • 5
    • 23244447184 scopus 로고    scopus 로고
    • Multiple imputation under Bayesianly smoothed pattern-mixture models for non-ignorable drop-out
    • H. Demirtas, Multiple imputation under Bayesianly smoothed pattern-mixture models for non-ignorable drop-out, Statist. Med. 24 (2005), pp. 2345-2363.
    • (2005) Statist. Med. , vol.24 , pp. 2345-2363
    • Demirtas, H.1
  • 6
    • 34547471668 scopus 로고    scopus 로고
    • Practical advice on how to impute continuous data when the ultimate interest centers on dichotomized outcomes through pre-specified thresholds
    • H. Demirtas, Practical advice on how to impute continuous data when the ultimate interest centers on dichotomized outcomes through pre-specified thresholds, Commun. Statist.-Simulation Comput. 36 (2007), pp. 871-889.
    • (2007) Commun. Statist.-Simulation Comput. , vol.36 , pp. 871-889
    • Demirtas, H.1
  • 7
    • 33846837287 scopus 로고    scopus 로고
    • Gaussianization-based quasi-imputation and expansion strategies for incomplete correlated binary responses
    • H. Demirtas and D. Hedeker, Gaussianization-based quasi-imputation and expansion strategies for incomplete correlated binary responses, Statist. Med. 26 (2007), pp. 782-799.
    • (2007) Statist. Med. , vol.26 , pp. 782-799
    • Demirtas, H.1    Hedeker, D.2
  • 8
    • 0042066687 scopus 로고    scopus 로고
    • On the performance of random-coefficient pattern-mixture models for non-ignorable drop-out
    • H. Demirtas and J.L. Schafer, On the performance of random-coefficient pattern-mixture models for non-ignorable drop-out, Statist. Med. 22 (2003), pp. 2253-2575.
    • (2003) Statist. Med. , vol.22 , pp. 2253-2575
    • Demirtas, H.1    Schafer, J.L.2
  • 9
    • 33947702607 scopus 로고    scopus 로고
    • On the performance of bias-reduction techniques for variance estimation in approximate Bayesian bootstrap imputation
    • H. Demirtas, L.M. Arguelles, H. Chung, and D. Hedeker, On the performance of bias-reduction techniques for variance estimation in approximate Bayesian bootstrap imputation, Comput. Statist. Data Anal. 51 (2007), pp. 4064-4068.
    • (2007) Comput. Statist. Data Anal. , vol.51 , pp. 4064-4068
    • Demirtas, H.1    Arguelles, L.M.2    Chung, H.3    Hedeker, D.4
  • 10
    • 38349186156 scopus 로고    scopus 로고
    • Plausibility of multivariate normality assumption when multiply imputing non-Gaussian continuous outcomes: A simulation assessment
    • H. Demirtas, S.A. Freels, and R.M. Yucel, Plausibility of multivariate normality assumption when multiply imputing non-Gaussian continuous outcomes: A simulation assessment, J. Statist. Comput. Simulation 78 (2008), pp. 69-84.
    • (2008) J. Statist. Comput. Simulation , vol.78 , pp. 69-84
    • Demirtas, H.1    Freels, S.A.2    Yucel, R.M.3
  • 11
    • 34250686456 scopus 로고    scopus 로고
    • Multiple imputation: Review of theory, implementation and software
    • O. Harel and X.H. Zhou, Multiple imputation: review of theory, implementation and software, Statist. Med. 26 (2007), pp. 3057-3077.
    • (2007) Statist. Med. , vol.26 , pp. 3057-3077
    • Harel, O.1    Zhou, X.H.2
  • 12
    • 0028650772 scopus 로고
    • A random-effects ordinal regression model for multilevel analysis
    • D. Hedeker and R.D. Gibbons, A random-effects ordinal regression model for multilevel analysis, Biometrics 50 (1994), pp. 933-944.
    • (1994) Biometrics , vol.50 , pp. 933-944
    • Hedeker, D.1    Gibbons, R.D.2
  • 13
    • 0002105479 scopus 로고    scopus 로고
    • Application of random effects pattern-mixture models for missing data in longitudinal studies
    • D. Hedeker and R.D. Gibbons, Application of random effects pattern-mixture models for missing data in longitudinal studies, Psychol. Methods 2 (1997), pp. 64-78.
    • (1997) Psychol. Methods , vol.2 , pp. 64-78
    • Hedeker, D.1    Gibbons, R.D.2
  • 14
    • 33846873244 scopus 로고    scopus 로고
    • Much ado about nothing: A comparison of missing data methods and software to fit incomplete data regression models
    • N.J. Horton and K.P. Kleinman, Much ado about nothing: A comparison of missing data methods and software to fit incomplete data regression models, Amer. Statist. 61 (2007), pp. 79-90.
    • (2007) Amer. Statist. , vol.61 , pp. 79-90
    • Horton, N.J.1    Kleinman, K.P.2
  • 15
    • 0242710940 scopus 로고    scopus 로고
    • A potential bias when rounding in multiple imputation
    • N.J. Horton, S.R. Lipsitz, and M. Parzen, A potential bias when rounding in multiple imputation, Amer. Statist. 57 (2003), pp. 229-232.
    • (2003) Amer. Statist. , vol.57 , pp. 229-232
    • Horton, N.J.1    Lipsitz, S.R.2    Parzen, M.3
  • 16
    • 0020333131 scopus 로고
    • Random-effects models for longitudinal data
    • N.M. Laird and J.H. Ware, Random-effects models for longitudinal data, Biometrics 38 (1982), pp. 963-974.
    • (1982) Biometrics , vol.38 , pp. 963-974
    • Laird, N.M.1    Ware, J.H.2
  • 18
    • 0000317187 scopus 로고
    • Multivariate correlation models with mixed discrete and continuous variables
    • I. Olkin and R.F. Tate, Multivariate correlation models with mixed discrete and continuous variables, Ann. Math. Statist., 32 (1961), pp. 448-465.
    • (1961) Ann. Math. Statist. , vol.32 , pp. 448-465
    • Olkin, I.1    Tate, R.F.2
  • 20
    • 0017133178 scopus 로고
    • Inference and missing data
    • D.B. Rubin, Inference and missing data, Biometrika 21 (1976), pp. 581-592.
    • (1976) Biometrika , vol.21 , pp. 581-592
    • Rubin, D.B.1
  • 21
    • 0030539070 scopus 로고    scopus 로고
    • Multiple imputation after 18+ years (with discussion)
    • D.B. Rubin, Multiple imputation after 18+ years (with discussion), J.Amer. Statist.Assoc. 91 (1996), pp. 473-520.
    • (1996) J. Amer. Statist. Assoc. , vol.91 , pp. 473-520
    • Rubin, D.B.1
  • 24
  • 26
    • 34347407592 scopus 로고    scopus 로고
    • Multiple imputation of discrete and continuous data by fully conditional specification
    • S. van Buuren, Multiple imputation of discrete and continuous data by fully conditional specification, Statist. Meth. Med. Res. 16 (2007), pp. 219-242.
    • (2007) Statist. Meth. Med. Res. , vol.16 , pp. 219-242
    • van Buuren, S.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.