메뉴 건너뛰기




Volumn 167, Issue 7, 2013, Pages 656-661

Missing data and multiple imputation

Author keywords

[No Author keywords available]

Indexed keywords

ACCURACY; CONFIDENCE INTERVAL; DATA ANALYSIS; PLANNING; PRIORITY JOURNAL; PROBABILITY; RANDOMIZATION; REVIEW; STATISTICAL ANALYSIS;

EID: 84880311538     PISSN: 21686203     EISSN: None     Source Type: Journal    
DOI: 10.1001/jamapediatrics.2013.1329     Document Type: Review
Times cited : (129)

References (29)
  • 1
    • 0025885661 scopus 로고
    • Biased estimation of the odds ratio in case-control studies due to the use of ad hoc methods of correcting for missing values for confounding variables
    • VachW, Blettner M. Biased estimation of the odds ratio in case-control studies due to the use of ad hoc methods of correcting for missing values for confounding variables. Am J Epidemiol. 1991;134(8): 895-907.
    • (1991) Am J Epidemiol. , vol.134 , Issue.8 , pp. 895-907
    • Vach, W.1    Blettner, M.2
  • 2
    • 0029584587 scopus 로고
    • A critical look at methods for handlingmissing covariates in epidemiologic regression analyses
    • Greenland S, FinkleWD. A critical look at methods for handlingmissing covariates in epidemiologic regression analyses. Am J Epidemiol. 1995;142(12):1255-1264.
    • (1995) Am J Epidemiol. , vol.142 , Issue.12 , pp. 1255-1264
    • Greenland, S.1    Finkle, W.D.2
  • 5
    • 78649551872 scopus 로고    scopus 로고
    • Bias and efficiency of multiple imputation compared with complete-case analysis for missing covariate values
    • White IR, Carlin JB. Bias and efficiency of multiple imputation compared with complete-case analysis for missing covariate values. Stat Med. 2010;29(28):2920-2931.
    • (2010) Stat Med. , vol.29 , Issue.28 , pp. 2920-2931
    • White, I.R.1    Carlin, J.B.2
  • 6
    • 0036224591 scopus 로고    scopus 로고
    • Impact ofmissing data due to selective dropouts in cohort studies and clinical trials
    • Touloumi G, Pocock SJ, Babiker AG, Darbyshire JH. Impact ofmissing data due to selective dropouts in cohort studies and clinical trials. Epidemiology. 2002;13(3):347-355.
    • (2002) Epidemiology. , vol.13 , Issue.3 , pp. 347-355
    • Touloumi, G.1    Pocock, S.J.2    Babiker, A.G.3    Darbyshire, J.H.4
  • 7
    • 77955896455 scopus 로고    scopus 로고
    • Strategies for multiple imputation in longitudinal studies
    • SprattM, Carpenter J, Sterne JA, et al. Strategies for multiple imputation in longitudinal studies. Am J Epidemiol. 2010;172(4):478-487.
    • (2010) Am J Epidemiol. , vol.172 , Issue.4 , pp. 478-487
    • Spratt, M.1    Carpenter, J.2    Sterne, J.A.3
  • 8
    • 34347396774 scopus 로고    scopus 로고
    • Multiple imputation: Current perspectives
    • Kenward MG, Carpenter J. Multiple imputation: current perspectives. Stat Methods Med Res. 2007;16(3):199-218.
    • (2007) Stat Methods Med Res. , vol.16 , Issue.3 , pp. 199-218
    • Kenward, M.G.1    Carpenter, J.2
  • 9
    • 84950455641 scopus 로고
    • Regression with missing X's: A review
    • Little RJA. Regression with missing X's: a review. J AmStat Assoc. 1992;87(12):1227-1237.
    • (1992) J AmStat Assoc. , vol.87 , Issue.12 , pp. 1227-1237
    • Little, R.J.A.1
  • 10
    • 0032960273 scopus 로고    scopus 로고
    • Multiple imputation: A primer
    • Schafer JL. Multiple imputation: a primer. Stat Methods Med Res. 1999;8(1):3-15.
    • (1999) Stat Methods Med Res. , vol.8 , Issue.1 , pp. 3-15
    • Schafer, J.L.1
  • 13
    • 0035755636 scopus 로고    scopus 로고
    • A comparison of inclusive and restrictive strategies in modern missing data procedures
    • Collins LM, Schafer JL, Kam CM. A comparison of inclusive and restrictive strategies in modern missing data procedures. Psychol Methods. 2001;6(4):330-351.
    • (2001) Psychol Methods. , vol.6 , Issue.4 , pp. 330-351
    • Collins, L.M.1    Schafer, J.L.2    Kam, C.M.3
  • 14
    • 33748709502 scopus 로고    scopus 로고
    • Using the outcome for imputation ofmissing predictor values was preferred
    • Moons KG, Donders RA, Stijnen T, Harrell FE Jr. Using the outcome for imputation ofmissing predictor values was preferred. J Clin Epidemiol. 2006;59(10):1092-1101.
    • (2006) J Clin Epidemiol. , vol.59 , Issue.10 , pp. 1092-1101
    • Moons, K.G.1    Donders, R.A.2    Stijnen, T.3    Harrell Jr., F.E.4
  • 15
    • 68249114452 scopus 로고    scopus 로고
    • Multiple imputation for missing data in epidemiological and clinical research: Potential and pitfalls
    • doi:10. 1136/bmj. b2393
    • Sterne JAC, White IR, Carlin JB, et al. Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls. BMJ. 2009;338:b2393. doi:10. 1136/bmj. b2393.
    • (2009) BMJ , vol.338
    • Sterne, J.A.C.1    White, I.R.2    Carlin, J.B.3
  • 16
    • 0025801348 scopus 로고
    • Multiple imputation in health-care databases: An overview and some applications
    • Rubin DB, Schenker N. Multiple imputation in health-care databases: an overview and some applications. Stat Med. 1991;10(4):585-598.
    • (1991) Stat Med. , vol.10 , Issue.4 , pp. 585-598
    • Rubin, D.B.1    Schenker, N.2
  • 17
    • 2142647296 scopus 로고    scopus 로고
    • What do we do with missing data? some options for analysis of incomplete data
    • Raghunathan TE. What do we do with missing data? some options for analysis of incomplete data. Annu Rev Public Health. 2004;25:99-117.
    • (2004) Annu Rev Public Health. , vol.25 , pp. 99-117
    • Raghunathan, T.E.1
  • 18
    • 84878516633 scopus 로고    scopus 로고
    • Review of inverse probability weighting for dealing with missing data [published online January 10, 2011]
    • doi:10. 1177/0962280210395740
    • Seaman SR, White IR. Review of inverse probability weighting for dealing with missing data [published online January 10, 2011]. Stat Methods Med Res. doi:10. 1177/0962280210395740.
    • Stat Methods Med Res.
    • Seaman, S.R.1    White, I.R.2
  • 19
    • 84874501270 scopus 로고    scopus 로고
    • On weighting approaches for missing data
    • doi:10. 1177/0962280211403597
    • Li L, Shen C, Li X, Robins JM. On weighting approaches for missing data. Stat Methods Med Res. 2013;22(1):14-30. doi:10. 1177/0962280211403597.
    • (2013) Stat Methods Med Res. , vol.22 , Issue.1 , pp. 14-30
    • Li, L.1    Shen, C.2    Li, X.3    Robins, J.M.4
  • 20
    • 84864817853 scopus 로고    scopus 로고
    • Missing covariate data in clinical research: When and when not to use themissing-indicator method for analysis
    • Groenwold RH, White IR, Donders AR, Carpenter JR, Altman DG, Moons KG. Missing covariate data in clinical research: when and when not to use themissing-indicator method for analysis. CMAJ. 2012;184(11):1265-1269.
    • (2012) CMAJ , vol.184 , Issue.11 , pp. 1265-1269
    • Groenwold, R.H.1    White, I.R.2    Donders, A.R.3    Carpenter, J.R.4    Altman, D.G.5    Moons, K.G.6
  • 22
    • 78651256743 scopus 로고    scopus 로고
    • Multiple imputation using chained equations: Issues and guidance for practice
    • White IR, Royston P, Wood AM. Multiple imputation using chained equations: issues and guidance for practice. Stat Med. 2011;30(4): 377-399.
    • (2011) Stat Med. , vol.30 , Issue.4 , pp. 377-399
    • White, I.R.1    Royston, P.2    Wood, A.M.3
  • 23
    • 84971580244 scopus 로고
    • Absence of evidence is not evidence of absence
    • Altman DG, Bland JM. Absence of evidence is not evidence of absence. BMJ. 1995;311(7003):485.
    • (1995) BMJ , vol.311 , Issue.7003 , pp. 485
    • Altman, D.G.1    Bland, J.M.2
  • 24
    • 75849144677 scopus 로고    scopus 로고
    • P values vs estimates of association with confidence intervals
    • Cummings P, Koepsell TD. P values vs estimates of association with confidence intervals. Arch Pediatr Adolesc Med. 2010;164(2):193-196.
    • (2010) Arch Pediatr Adolesc Med. , vol.164 , Issue.2 , pp. 193-196
    • Cummings, P.1    Koepsell, T.D.2
  • 25
    • 83655163679 scopus 로고    scopus 로고
    • Berkson's bias, selection bias, and missing data
    • Westreich D. Berkson's bias, selection bias, and missing data. Epidemiology. 2012;23(1):159-164.
    • (2012) Epidemiology. , vol.23 , Issue.1 , pp. 159-164
    • Westreich, D.1
  • 26
    • 3042807973 scopus 로고    scopus 로고
    • Imputations of missing values in practice: Results from imputations of serum cholesterol in 28 cohort studies
    • Barzi F, WoodwardM. Imputations of missing values in practice: results from imputations of serum cholesterol in 28 cohort studies. Am J Epidemiol. 2004;160(1):34-45.
    • (2004) Am J Epidemiol. , vol.160 , Issue.1 , pp. 34-45
    • Barzi, F.1    Woodward, M.2
  • 27
    • 34347372013 scopus 로고    scopus 로고
    • A comparison of imputation techniques for handlingmissing predictor values in a risk model with a binary outcome
    • Ambler G, Omar RZ, Royston P. A comparison of imputation techniques for handlingmissing predictor values in a risk model with a binary outcome. Stat Methods Med Res. 2007;16(3): 277-298.
    • (2007) Stat Methods Med Res. , vol.16 , Issue.3 , pp. 277-298
    • Ambler, G.1    Omar, R.Z.2    Royston, P.3
  • 28
    • 33744830564 scopus 로고    scopus 로고
    • Can one assess whether missing data are missing at random in medical studies?
    • Potthoff RF, Tudor GE, Pieper KS, Hasselblad V. Can one assess whether missing data are missing at random in medical studies? Stat Methods Med Res. 2006;15(3):213-234.
    • (2006) Stat Methods Med Res , vol.15 , Issue.3 , pp. 213-234
    • Potthoff, R.F.1    Tudor, G.E.2    Pieper, K.S.3    Hasselblad, V.4
  • 29
    • 79551622288 scopus 로고    scopus 로고
    • Addressing missing data in clinical trials
    • Fleming TR. Addressing missing data in clinical trials. Ann Intern Med. 2011;154(2):113-117.
    • (2011) Ann Intern Med. , vol.154 , Issue.2 , pp. 113-117
    • Fleming, T.R.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.