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Volumn 28, Issue 3, 2017, Pages 387-395

Matching weights to simultaneously compare three treatment groups comparison to three-way matching

Author keywords

[No Author keywords available]

Indexed keywords

CYCLOOXYGENASE 2 INHIBITOR; NONSTEROID ANTIINFLAMMATORY AGENT; ANALGESIC AGENT; NARCOTIC ANALGESIC AGENT; PROSTAGLANDIN SYNTHASE INHIBITOR;

EID: 85011663032     PISSN: 10443983     EISSN: 15315487     Source Type: Journal    
DOI: 10.1097/EDE.0000000000000627     Document Type: Article
Times cited : (115)

References (29)
  • 1
    • 0019259065 scopus 로고
    • Control of confounding in the assessment of medical technology
    • Greenland S, Neutra R. Control of confounding in the assessment of medical technology. Int J Epidemiol. 1980;9:361-367.
    • (1980) Int J Epidemiol , vol.9 , pp. 361-367
    • Greenland, S.1    Neutra, R.2
  • 2
    • 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
  • 4
    • 0000724291 scopus 로고    scopus 로고
    • The role of the propensity score in estimating dose-response functions
    • Imbens GW. The role of the propensity score in estimating dose-response functions. Biometrika. 2000;87:706-710.
    • (2000) Biometrika , vol.87 , pp. 706-710
    • Imbens, G.W.1
  • 5
    • 33745842238 scopus 로고    scopus 로고
    • Estimating causal effects from epidemiological data
    • Hernán MA, Robins JM. Estimating causal effects from epidemiological data. J Epidemiol Community Health. 2006;60:578-586.
    • (2006) J Epidemiol Community Health , vol.60 , pp. 578-586
    • Hernán, M.A.1    Robins, J.M.2
  • 6
    • 84896544710 scopus 로고    scopus 로고
    • A weighting analogue to pair matching in propensity score analysis
    • Li L, Greene T. A weighting analogue to pair matching in propensity score analysis. Int J Biostat. 2013;9:215-234.
    • (2013) Int J Biostat , vol.9 , pp. 215-234
    • Li, L.1    Greene, T.2
  • 7
    • 0033839024 scopus 로고    scopus 로고
    • Marginal structural models to estimate the causal effect of zidovudine on the survival of HIV-positive men
    • Hernán MA, Brumback B, Robins JM. Marginal structural models to estimate the causal effect of zidovudine on the survival of HIV-positive men. Epidemiology. 2000;11:561-570.
    • (2000) Epidemiology , vol.11 , pp. 561-570
    • Hernán, M.A.1    Brumback, B.2    Robins, J.M.3
  • 8
    • 0035761721 scopus 로고    scopus 로고
    • Estimation of causal effects using propensity score weighting: An application to data on right heart catheterization
    • Hirano K, Imbens GW. Estimation of causal effects using propensity score weighting: An application to data on right heart catheterization. Health Serv Outcomes Res Methodol. 2001;2:259-278.
    • (2001) Health Serv Outcomes Res Methodol , vol.2 , pp. 259-278
    • Hirano, K.1    Imbens, G.W.2
  • 9
    • 1542472967 scopus 로고    scopus 로고
    • Marginal structural models as a tool for standardization
    • Sato T, Matsuyama Y. Marginal structural models as a tool for standardization. Epidemiology. 2003;14:680-686.
    • (2003) Epidemiology , vol.14 , pp. 680-686
    • Sato, T.1    Matsuyama, Y.2
  • 10
    • 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. Rev Econ Stat. 2004;86:4-29.
    • (2004) Rev Econ Stat , vol.86 , pp. 4-29
    • Imbens, G.W.1
  • 11
    • 77149125892 scopus 로고    scopus 로고
    • Use of stabilized inverse propensity scores as weights to directly estimate relative risk and its confidence intervals
    • Xu S, Ross C, Raebel MA, Shetterly S, Blanchette C, Smith D. Use of stabilized inverse propensity scores as weights to directly estimate relative risk and its confidence intervals. Value Health. 2010;13:273-277.
    • (2010) Value Health , vol.13 , pp. 273-277
    • Xu, S.1    Ross, C.2    Raebel, M.A.3    Shetterly, S.4    Blanchette, C.5    Smith, D.6
  • 13
    • 0002864224 scopus 로고    scopus 로고
    • Confounding and collapsibility in causal inference
    • Greenland S, Robins JM, Pearl J. Confounding and collapsibility in causal inference. Statist Sci. 1999;14:29-46.
    • (1999) Statist Sci , vol.14 , pp. 29-46
    • Greenland, S.1    Robins, J.M.2    Pearl, J.3
  • 14
    • 66149131082 scopus 로고    scopus 로고
    • The relative merits of risk ratios and odds ratios
    • Cummings P. The relative merits of risk ratios and odds ratios. Arch Pediatr Adolesc Med. 2009;163:438-445.
    • (2009) Arch Pediatr Adolesc Med , vol.163 , pp. 438-445
    • Cummings, P.1
  • 16
    • 1642420994 scopus 로고    scopus 로고
    • A modified Poisson regression approach to prospective studies with binary data
    • Zou G. A modified Poisson regression approach to prospective studies with binary data. Am J Epidemiol. 2004;159:702-706.
    • (2004) Am J Epidemiol , vol.159 , pp. 702-706
    • Zou, G.1
  • 18
    • 84947396376 scopus 로고
    • A generalization of sampling without replacement from a finite universe
    • Horvitz DG, Thompson DJ. A generalization of sampling without replacement from a finite universe. J Am Stat Assoc. 1952;47:663-685.
    • (1952) J Am Stat Assoc , vol.47 , pp. 663-685
    • Horvitz, D.G.1    Thompson, D.J.2
  • 19
    • 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 Behav Res. 2011;46:399-424.
    • (2011) Multivariate Behav Res , vol.46 , pp. 399-424
    • Austin, P.C.1
  • 20
    • 84944796673 scopus 로고    scopus 로고
    • Moving towards best practice when using inverse probability of treatment weighting (IPTW) using the propensity score to estimate causal treatment effects in observational studies
    • Austin PC, Stuart EA. Moving towards best practice when using inverse probability of treatment weighting (IPTW) using the propensity score to estimate causal treatment effects in observational studies. Stat Med. 2015;34:3661-3679.
    • (2015) Stat Med , vol.34 , pp. 3661-3679
    • Austin, P.C.1    Stuart, E.A.2
  • 21
    • 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. Stat Med. 2014;33:4306-4319.
    • (2014) Stat Med , vol.33 , pp. 4306-4319
    • Austin, P.C.1    Small, D.S.2
  • 22
    • 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. Stat Sci. 2010;25:1-21.
    • (2010) Stat Sci , vol.25 , pp. 1-21
    • Stuart, E.A.1
  • 24
    • 84933676446 scopus 로고    scopus 로고
    • Active-comparator design and newuser design in observational studies
    • Yoshida K, Solomon DH, Kim SC. Active-comparator design and newuser design in observational studies. Nat Rev Rheumatol. 2015;11:437- 441.
    • (2015) Nat Rev Rheumatol , vol.11 , pp. 437-441
    • Yoshida, K.1    Solomon, D.H.2    Kim, S.C.3
  • 25
    • 0033847784 scopus 로고    scopus 로고
    • Marginal structural models and causal inference in epidemiology
    • Robins JM, Hernán MA, Brumback B. Marginal structural models and causal inference in epidemiology. Epidemiology. 2000;11:550-560.
    • (2000) Epidemiology , vol.11 , pp. 550-560
    • Robins, J.M.1    Hernán, M.A.2    Brumback, B.3
  • 27
    • 60449086859 scopus 로고    scopus 로고
    • Dealing with limited overlap in estimation of average treatment effects
    • Crump RK, Hotz VJ, Imbens GW, Mitnik OA. Dealing with limited overlap in estimation of average treatment effects. Biometrika. 2009;96:187- 199.
    • (2009) Biometrika , vol.96 , pp. 187-199
    • Crump, R.K.1    Hotz, V.J.2    Imbens, G.W.3    Mitnik, O.A.4
  • 28
    • 77957301897 scopus 로고    scopus 로고
    • Treatment effects in the presence of unmeasured confounding: Dealing with observations in the tails of the propensity score distribution-Asimulation study
    • Stürmer T, Rothman KJ, Avorn J, Glynn RJ. Treatment effects in the presence of unmeasured confounding: dealing with observations in the tails of the propensity score distribution-Asimulation study. Am J Epidemiol. 2010;172:843-854.
    • (2010) Am J Epidemiol , vol.172 , pp. 843-854
    • Stürmer, T.1    Rothman, K.J.2    Avorn, J.3    Glynn, R.J.4
  • 29
    • 84888314733 scopus 로고    scopus 로고
    • A tool for assessing the feasibility of comparative effectiveness research
    • Walker A, Patrick, Lauer, et al. A tool for assessing the feasibility of comparative effectiveness research. Comp Eff Res. 2013;2013:11-20.
    • (2013) Comp Eff Res , vol.2013 , pp. 11-20
    • Walker, A.1    Patrick, L.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.