메뉴 건너뛰기




Volumn 34, Issue 30, 2015, Pages 3949-3967

Optimal full matching for survival outcomes: a method that merits more widespread use

Author keywords

bias; full matching; matching; Monte Carlo simulations; observational studies; optimal matching; propensity score

Indexed keywords

AGED; ALGORITHM; ARTICLE; CASE STUDY; CONFIDENCE INTERVAL; CONTROLLED STUDY; ERROR; FEMALE; HEART INFARCTION; HOSPITAL DISCHARGE; HUMAN; MAJOR CLINICAL STUDY; MALE; MATHEMATICAL ANALYSIS; MONTE CARLO METHOD; MORTALITY; NEAREST NEIGHBOR CALIPER MATCHING; NEAREST NEIGHBOR MATCHING; OBSERVATIONAL STUDY; OPTIMAL FULL MATCHING; PROBABILITY; PROPENSITY SCORE; REGRESSION ANALYSIS; STATISTICAL ANALYSIS; SURVIVAL; SURVIVAL ANALYSIS; TREATMENT OUTCOME; BIOSTATISTICS; CASE CONTROL STUDY; COMPUTER SIMULATION; MYOCARDIAL INFARCTION; OUTCOME ASSESSMENT; PROCEDURES; PROPORTIONAL HAZARDS MODEL; STATISTICAL MODEL; STATISTICS AND NUMERICAL DATA;

EID: 84938629257     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.6602     Document Type: Article
Times cited : (77)

References (57)
  • 1
    • 1842429563 scopus 로고    scopus 로고
    • Nonparametric estimation of average treatment effects under exogeneity: a review
    • Imbens GW. Nonparametric estimation of average treatment effects under exogeneity: a review. Review of Economics and Statistics. 2004; 86: 4–29.
    • (2004) Review of Economics and Statistics , vol.86 , pp. 4-29
    • Imbens, G.W.1
  • 2
    • 84856187945 scopus 로고    scopus 로고
    • Causal inference without balance checking: coarsened exact matching
    • Iacus SM, King G, Porro G. Causal inference without balance checking: coarsened exact matching. Political Analysis. 2012; 20(1):1–24.
    • (2012) Political Analysis , vol.20 , Issue.1 , pp. 1-24
    • Iacus, S.M.1    King, G.2    Porro, G.3
  • 3
    • 0003138938 scopus 로고
    • Comparison of multivariate matching methods: structures, distances, and algorithms
    • Gu XS, Rosenbaum PR. Comparison of multivariate matching methods: structures, distances, and algorithms. Journal of Computational and Graphical Statistics. 1993; 2:405–420.
    • (1993) Journal of Computational and Graphical Statistics , vol.2 , pp. 405-420
    • Gu, X.S.1    Rosenbaum, P.R.2
  • 4
    • 77957806232 scopus 로고    scopus 로고
    • Matching methods for causal inference: a review and a look forward
    • Stuart EA. Matching methods for causal inference: a review and a look forward. Statistical Science. 2010; 25(1):1–21.
    • (2010) Statistical Science , vol.25 , Issue.1 , pp. 1-21
    • Stuart, E.A.1
  • 5
    • 77951622706 scopus 로고
    • The central role of the propensity score in observational studies for causal effects
    • Rosenbaum PR, Rubin DB. The central role of the propensity score in observational studies for causal effects. Biometrika. 1983; 70:41–55.
    • (1983) Biometrika , vol.70 , pp. 41-55
    • Rosenbaum, P.R.1    Rubin, D.B.2
  • 6
    • 44649173785 scopus 로고    scopus 로고
    • A critical appraisal of propensity-score matching in the medical literature between 1996 and 2003
    • Austin PC. A critical appraisal of propensity-score matching in the medical literature between 1996 and 2003. Statistics in Medicine. 2008; 27(12):2037–2049.
    • (2008) Statistics in Medicine , vol.27 , Issue.12 , pp. 2037-2049
    • Austin, P.C.1
  • 7
    • 67249139797 scopus 로고    scopus 로고
    • A report card on propensity-score matching in the cardiology literature from 2004 to 2006: a systematic review and suggestions for improvement
    • Austin PC. A report card on propensity-score matching in the cardiology literature from 2004 to 2006: a systematic review and suggestions for improvement. Circulation: Cardiovascular Quality and Outcomes. 2008; 1:62–67.
    • (2008) Circulation: Cardiovascular Quality and Outcomes , vol.1 , pp. 62-67
    • Austin, P.C.1
  • 8
    • 35448972461 scopus 로고    scopus 로고
    • Propensity-score matching in the cardiovascular surgery literature from 2004 to 2006: a systematic review and suggestions for improvement
    • Austin PC. Propensity-score matching in the cardiovascular surgery literature from 2004 to 2006: a systematic review and suggestions for improvement. Journal of Thoracic and Cardiovascular Surgery. 2007; 134(5):1128–1135.
    • (2007) Journal of Thoracic and Cardiovascular Surgery , vol.134 , Issue.5 , pp. 1128-1135
    • Austin, P.C.1
  • 9
    • 0034100672 scopus 로고    scopus 로고
    • Substantial gains in bias reduction from matching with a variable number of controls
    • Ming K, Rosenbaum PR. Substantial gains in bias reduction from matching with a variable number of controls. Biometrics. 2000; 56(1):118–124.
    • (2000) Biometrics , vol.56 , Issue.1 , pp. 118-124
    • Ming, K.1    Rosenbaum, P.R.2
  • 10
    • 77958523826 scopus 로고    scopus 로고
    • Statistical criteria for selecting the optimal number of untreated subjects matched to each treated subject when using many-to-one matching on the propensity score
    • Austin PC. Statistical criteria for selecting the optimal number of untreated subjects matched to each treated subject when using many-to-one matching on the propensity score. American Journal of Epidemiology. 2010; 172(9):1092–1097.
    • (2010) American Journal of Epidemiology , vol.172 , Issue.9 , pp. 1092-1097
    • Austin, P.C.1
  • 12
    • 84945581878 scopus 로고
    • Constructing a control group using multivariate matched sampling methods that incorporate the propensity score
    • Rosenbaum PR, Rubin DB. Constructing a control group using multivariate matched sampling methods that incorporate the propensity score. The American Statistician. 1985; 39:33–38.
    • (1985) The American Statistician , vol.39 , pp. 33-38
    • Rosenbaum, P.R.1    Rubin, D.B.2
  • 13
    • 84893777424 scopus 로고    scopus 로고
    • A comparison of 12 algorithms for matching on the propensity score
    • Austin PC. A comparison of 12 algorithms for matching on the propensity score. Statisics in Medicine. 2014; 33(6):1057–1069.
    • (2014) Statisics in Medicine , vol.33 , Issue.6 , pp. 1057-1069
    • Austin, P.C.1
  • 14
    • 33645226210 scopus 로고    scopus 로고
    • A review of the application of propensity score methods yielded increasing use, advantages in specific settings, but not substantially different estimates compared with conventional multivariable methods
    • Sturmer T, Joshi M, Glynn RJ, Avorn J, Rothman KJ, Schneeweiss S. A review of the application of propensity score methods yielded increasing use, advantages in specific settings, but not substantially different estimates compared with conventional multivariable methods. Journal of Clinical Epidemiology. 2006; 59(5):437–447.
    • (2006) Journal of Clinical Epidemiology , vol.59 , Issue.5 , pp. 437-447
    • Sturmer, T.1    Joshi, M.2    Glynn, R.J.3    Avorn, J.4    Rothman, K.J.5    Schneeweiss, S.6
  • 15
    • 4944238507 scopus 로고    scopus 로고
    • Full matching in an observational study of coaching for the SAT
    • Hansen BB. Full matching in an observational study of coaching for the SAT. Journal of the American Statistical Association. 2004; 99(467):609–618.
    • (2004) Journal of the American Statistical Association , vol.99 , Issue.467 , pp. 609-618
    • Hansen, B.B.1
  • 17
    • 72749123968 scopus 로고    scopus 로고
    • A substantial and confusing variation exists in handling of baseline covariates in randomized controlled trials: a review of trials published in leading medical journals
    • Austin PC, Manca A, Zwarenstein M, Juurlink DN, Stanbrook MB. A substantial and confusing variation exists in handling of baseline covariates in randomized controlled trials: a review of trials published in leading medical journals. Journal of Clinical Epidemiology. 2010; 63(2):142–153.
    • (2010) Journal of Clinical Epidemiology , vol.63 , Issue.2 , pp. 142-153
    • Austin, P.C.1    Manca, A.2    Zwarenstein, M.3    Juurlink, D.N.4    Stanbrook, M.B.5
  • 20
    • 84869079202 scopus 로고    scopus 로고
    • Two propensity score-based strategies for a three-decade observational study: investigating psychotropic medications and suicide risk
    • Leon AC, Demirtas H, Li C, Hedeker D. Two propensity score-based strategies for a three-decade observational study: investigating psychotropic medications and suicide risk. Statistics in Medicine. 2012; 31(27):3255–3260.
    • (2012) Statistics in Medicine , vol.31 , Issue.27 , pp. 3255-3260
    • Leon, A.C.1    Demirtas, H.2    Li, C.3    Hedeker, D.4
  • 23
    • 84949193513 scopus 로고
    • Reducing bias in observational studies using subclassification on the propensity score
    • Rosenbaum PR, Rubin DB. Reducing bias in observational studies using subclassification on the propensity score. Journal of the American Statistical Association. 1984; 79:516–524.
    • (1984) Journal of the American Statistical Association , vol.79 , pp. 516-524
    • Rosenbaum, P.R.1    Rubin, D.B.2
  • 24
    • 79951791644 scopus 로고    scopus 로고
    • A tutorial and case study in propensity score analysis: an application to estimating the effect of in-hospital smoking cessation counseling on mortality
    • Austin PC. A tutorial and case study in propensity score analysis: an application to estimating the effect of in-hospital smoking cessation counseling on mortality. Multivariate Behavioral Research. 2011; 46:119–151.
    • (2011) Multivariate Behavioral Research , vol.46 , pp. 119-151
    • Austin, P.C.1
  • 25
    • 79958704133 scopus 로고    scopus 로고
    • An introduction to propensity-score methods for reducing the effects of confounding in observational studies
    • Austin PC. An introduction to propensity-score methods for reducing the effects of confounding in observational studies. Multivariate Behavioral Research. 2011; 46:399–424.
    • (2011) Multivariate Behavioral Research , vol.46 , pp. 399-424
    • Austin, P.C.1
  • 26
    • 34249885738 scopus 로고    scopus 로고
    • Matching as nonparametric preprocessing for reducing model dependence in parametric causal inference
    • Ho DE, Imai K, King G, Stuart EA. Matching as nonparametric preprocessing for reducing model dependence in parametric causal inference. Political Analysis. 2007; 15:199–236.
    • (2007) Political Analysis , vol.15 , pp. 199-236
    • Ho, D.E.1    Imai, K.2    King, G.3    Stuart, E.A.4
  • 28
  • 29
    • 84879167098 scopus 로고    scopus 로고
    • The performance of different propensity score methods for estimating marginal hazard ratios
    • Austin PC. The performance of different propensity score methods for estimating marginal hazard ratios. Stastisics in Medicine. 2013; 32(16):2837–2849.
    • (2013) Stastisics in Medicine , vol.32 , Issue.16 , pp. 2837-2849
    • Austin, P.C.1
  • 30
    • 77956314484 scopus 로고    scopus 로고
    • The performance of different propensity-score methods for estimating differences in proportions (risk differences or absolute risk reductions) in observational studies
    • Austin PC. The performance of different propensity-score methods for estimating differences in proportions (risk differences or absolute risk reductions) in observational studies. Statistics in Medicine. 2010; 29(20):2137–2148.
    • (2010) Statistics in Medicine , vol.29 , Issue.20 , pp. 2137-2148
    • Austin, P.C.1
  • 31
    • 77958600686 scopus 로고    scopus 로고
    • Optimal caliper widths for propensity-score matching when estimating differences in means and differences in proportions in observational studies
    • Austin PC. Optimal caliper widths for propensity-score matching when estimating differences in means and differences in proportions in observational studies. Pharmaceutical Statistics. 2011; 10:150–161.
    • (2011) Pharmaceutical Statistics , vol.10 , pp. 150-161
    • Austin, P.C.1
  • 32
    • 33846813595 scopus 로고    scopus 로고
    • Conditioning on the propensity score can result in biased estimation of common measures of treatment effect: a Monte Carlo study
    • Austin PC, Grootendorst P, Normand SL, Anderson GM. Conditioning on the propensity score can result in biased estimation of common measures of treatment effect: a Monte Carlo study. Statistics in Medicine. 2007; 26(4):754–768.
    • (2007) Statistics in Medicine , vol.26 , Issue.4 , pp. 754-768
    • Austin, P.C.1    Grootendorst, P.2    Normand, S.L.3    Anderson, G.M.4
  • 33
    • 34249863765 scopus 로고    scopus 로고
    • The performance of different propensity score methods for estimating marginal odds ratios
    • Austin PC. The performance of different propensity score methods for estimating marginal odds ratios. Statistics in Medicine. 2007; 26(16):3078–3094.
    • (2007) Statistics in Medicine , vol.26 , Issue.16 , pp. 3078-3094
    • Austin, P.C.1
  • 34
    • 43049162150 scopus 로고    scopus 로고
    • The performance of different propensity-score methods for estimating relative risks
    • Austin PC. The performance of different propensity-score methods for estimating relative risks. Journal of Clinical Epidemiology. 2008; 61(6):537–545.
    • (2008) Journal of Clinical Epidemiology , vol.61 , Issue.6 , pp. 537-545
    • Austin, P.C.1
  • 35
    • 84908056108 scopus 로고    scopus 로고
    • The use of bootstrapping when using propensity-score matching without replacement: a simulation study
    • Austin PC, Small DS. The use of bootstrapping when using propensity-score matching without replacement: a simulation study. Statisics in Medicine. 2014; 33(24):4306–4319.
    • (2014) Statisics in Medicine , vol.33 , Issue.24 , pp. 4306-4319
    • Austin, P.C.1    Small, D.S.2
  • 36
    • 19944372078 scopus 로고    scopus 로고
    • Generating survival times to simulate Cox proportional hazards models
    • Bender R, Augustin T, Blettner M. Generating survival times to simulate Cox proportional hazards models. Statistics in Medicine. 2005; 24(11):1713–1723.
    • (2005) Statistics in Medicine , vol.24 , Issue.11 , pp. 1713-1723
    • Bender, R.1    Augustin, T.2    Blettner, M.3
  • 37
    • 77349087330 scopus 로고    scopus 로고
    • A data-generation process for data with specified risk differences or numbers needed to treat
    • Austin PC. A data-generation process for data with specified risk differences or numbers needed to treat. Communications in Statistics - Simulation and Computation. 2010; 39:563–577.
    • (2010) Communications in Statistics - Simulation and Computation , vol.39 , pp. 563-577
    • Austin, P.C.1
  • 38
    • 47749131861 scopus 로고    scopus 로고
    • The performance of two data-generation processes for data with specified marginal treatment odds ratios
    • Austin PC, Stafford J. The performance of two data-generation processes for data with specified marginal treatment odds ratios. Communications in Statistics - Simulation and Computation. 2008; 37:1039–1051.
    • (2008) Communications in Statistics - Simulation and Computation , vol.37 , pp. 1039-1051
    • Austin, P.C.1    Stafford, J.2
  • 39
    • 84861097401 scopus 로고    scopus 로고
    • Propensity score applied to survival data analysis through proportional hazards models: a Monte Carlo study
    • Gayat E, Resche-Rigon M, Mary JY, Porcher R. Propensity score applied to survival data analysis through proportional hazards models: a Monte Carlo study. Pharmaceutical Statistics. 2012; 11(3):222–229.
    • (2012) Pharmaceutical Statistics , vol.11 , Issue.3 , pp. 222-229
    • Gayat, E.1    Resche-Rigon, M.2    Mary, J.Y.3    Porcher, R.4
  • 40
  • 41
    • 33846842327 scopus 로고    scopus 로고
    • A comparison of the ability of different propensity score models to balance measured variables between treated and untreated subjects: a Monte Carlo study
    • Austin PC, Grootendorst P, Anderson GM. A comparison of the ability of different propensity score models to balance measured variables between treated and untreated subjects: a Monte Carlo study. Statistics in Medicine. 2007; 26(4):734–753.
    • (2007) Statistics in Medicine , vol.26 , Issue.4 , pp. 734-753
    • Austin, P.C.1    Grootendorst, P.2    Anderson, G.M.3
  • 42
    • 77958600686 scopus 로고    scopus 로고
    • Optimal caliper widths for propensity-score matching when estimating differences in means and differences in proportions in observational studies
    • Austin PC. Optimal caliper widths for propensity-score matching when estimating differences in means and differences in proportions in observational studies. Pharmaceutical Statistics. 2010; 10:150–161.
    • (2010) Pharmaceutical Statistics , vol.10 , pp. 150-161
    • Austin, P.C.1
  • 43
    • 8744315994 scopus 로고    scopus 로고
    • Model selection, confounder control, and marginal structural models: review and new applications
    • Joffe MM, Ten Have TR, Feldman HI, Kimmel SE. Model selection, confounder control, and marginal structural models: review and new applications. The American Statistician. 2004; 58:272–279.
    • (2004) The American Statistician , vol.58 , pp. 272-279
    • Joffe, M.M.1    Ten Have, T.R.2    Feldman, H.I.3    Kimmel, S.E.4
  • 44
    • 70449365700 scopus 로고    scopus 로고
    • Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples
    • Austin PC. Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples. Statistics in Medicine. 2009; 28(25):3083–3107.
    • (2009) Statistics in Medicine , vol.28 , Issue.25 , pp. 3083-3107
    • Austin, P.C.1
  • 48
    • 84896729825 scopus 로고    scopus 로고
    • The use of propensity score methods with survival or time-to-event outcomes: reporting measures of effect similar to those used in randomized experiments
    • Austin PC. The use of propensity score methods with survival or time-to-event outcomes: reporting measures of effect similar to those used in randomized experiments. Stastisics in Medicine. 2014; 33(7):1242–1258.
    • (2014) Stastisics in Medicine , vol.33 , Issue.7 , pp. 1242-1258
    • Austin, P.C.1
  • 50
    • 33745588280 scopus 로고    scopus 로고
    • Interval estimation for treatment effects using propensity score matching
    • Hill J, Reiter JP. Interval estimation for treatment effects using propensity score matching. Statistics in Medicine. 2006; 25(13):2230–2256.
    • (2006) Statistics in Medicine , vol.25 , Issue.13 , pp. 2230-2256
    • Hill, J.1    Reiter, J.P.2
  • 51
    • 84969402867 scopus 로고    scopus 로고
    • The performance of inverse probability of treatment weighting and full matching on the propensity score in the presence of model misspecification when estimating the effect of treatment on survival outcomes
    • Austin PC, Stuart EA. The performance of inverse probability of treatment weighting and full matching on the propensity score in the presence of model misspecification when estimating the effect of treatment on survival outcomes. Statistical Methods in Medical Research. 2015.
    • (2015) Statistical Methods in Medical Research
    • Austin, P.C.1    Stuart, E.A.2
  • 54
    • 0035761763 scopus 로고    scopus 로고
    • Using propensity scores to help design observational studies: application to the tobacco litigation
    • Rubin DB. Using propensity scores to help design observational studies: application to the tobacco litigation. Health Services & Outcomes Research Methodology. 2001; 2:169–188.
    • (2001) Health Services & Outcomes Research Methodology , vol.2 , pp. 169-188
    • Rubin, D.B.1
  • 55
    • 57749105474 scopus 로고    scopus 로고
    • Average causal effects from nonrandomized studies: a practical guide and simulated example
    • Schafer JL, Kang J. Average causal effects from nonrandomized studies: a practical guide and simulated example. Psychological Methods. 2008; 13(4):279–313.
    • (2008) Psychological Methods , vol.13 , Issue.4 , pp. 279-313
    • Schafer, J.L.1    Kang, J.2
  • 56
    • 46249131752 scopus 로고    scopus 로고
    • Demystifying double robustness: a comparison of alternative strategies for estimating a population mean from incomplete data
    • Kang J, Schafer J. Demystifying double robustness: a comparison of alternative strategies for estimating a population mean from incomplete data. Statistical Science. 2007; 22:523–580.
    • (2007) Statistical Science , vol.22 , pp. 523-580
    • Kang, J.1    Schafer, J.2
  • 57
    • 10844272375 scopus 로고    scopus 로고
    • On principles for modeling propensity scores in medical research
    • Rubin DB. On principles for modeling propensity scores in medical research. Pharmacoepidemiology and Drug Safety. 2004; 13(12):855–857.
    • (2004) Pharmacoepidemiology and Drug Safety , vol.13 , Issue.12 , pp. 855-857
    • Rubin, D.B.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.