참고문헌
- Newhouse JP, McClellan M. Econometrics in outcomes research: The use of instrumental variables. Annu Rev Pub Health 1998; 19: 17-34 https://doi.org/10.1146/annurev.publhealth.19.1.17
- Kaufman JS, Kaufman S, Poole C. Causal inference from randomized trials in social epidemiology. Soc Sci Med 2003; 57(12): 2397-2409 https://doi.org/10.1016/S0277-9536(03)00135-7
- Kaufman JS, Cooper RS. Seeking causal explanations in social epidemiology Am J Epidemiol 1999; 150(2): 113-120 https://doi.org/10.1093/oxfordjournals.aje.a009969
- Jary D, Jary J. HarperCollins Dictionary of Sociology. New York: HarperCollins Publishers, Ltd.; 1991
- Lewis D. Causation. J Philos 1973; 70(17): 556-567 https://doi.org/10.2307/2025310
- Maldonado G, Greenland S. Estimating causal effects. Int J Epidemiol 2002; 31(2): 422-429 https://doi.org/10.1093/ije/31.2.422
- Oakes JM, Johnson PJ. Propensity score matching for social epidemiology. In: Oakes JM, Kaufman JS, editors. Methods for Social Epidemiology. San Francisco: Jossey-Bass; 2006. p. 370-392
- McClellan M, McNeil BJ, Newhouse JP. Does more intensive treatment of acute myocardial infarction in the elderly reduce mortality? Analysis using instrumental variables. JAMA 1994; 272(11): 859-866 https://doi.org/10.1001/jama.272.11.859
- Zohoori N, Savitz DA. Econometric approaches to epidemiologic data: Relating endogeneity and unobserved heterogeneity to confounding. Ann Epidemiol 1997; 7(4): 251-257 https://doi.org/10.1016/S1047-2797(97)00023-9
- Luft HS, Hunt SS, Maerki SC. The volume-outcome relationship: Practice-makes-perfect or selective-referral patterns? Health Serv Res 1987; 22(2): 157-182
- Lee JY, Rozier RG, Norton EC, Vann WF Jr. Addressing selection bias in dental health services research. J Dent Res 2005; 84(10): 942-946 https://doi.org/10.1177/154405910508401013
- Rosenbaum PR, Rubin DB. The central role of the propensity score in observational studies for causal effects. Biometrika 1983; 70(1): 41-55 https://doi.org/10.1093/biomet/70.1.41
- D'Agostino RB Jr. Propensity score methods for bias reduction in the comparison of a treatment to a non-randomized control group. Stat Med 1998; 17(19): 2265-2281 https://doi.org/10.1002/(SICI)1097-0258(19981015)17:19<2265::AID-SIM918>3.0.CO;2-B
- Rubin DB. Estimating causal effects from large data sets using propensity scores. Ann Intern Med 1997; 127(8 Pt 2): 757-763 https://doi.org/10.7326/0003-4819-127-8_Part_2-199710151-00064
- Newhouse JP, McClellan M. Econometrics in outcomes research: The use of instrumental variables. Annu Rev Pub Health 1998; 19(1): 17-34 https://doi.org/10.1146/annurev.publhealth.19.1.17
- McClellan MB, Newhouse JP. Overview of the special supplement issue. Health Serv Res 2000; 35(5 Pt 2): 1061-1069
- Mennemeyer ST. Can econometrics rescue epidemiology? Ann Epidemiol 1997; 7(4): 249-250 https://doi.org/10.1016/S1047-2797(97)00021-5
- Zohoori N, Savitz DA. Econometric approaches to epidemiologic data: Relating endogeneity and unobserved heterogeneity to confounding. Ann Epidemiol 1997; 7(4): 251-257 https://doi.org/10.1016/S1047-2797(97)00023-9
- Greenland S. An introduction to instrumental variables for epidemiologists. Int J Epidemiol 2000; 29(4): 722-729 https://doi.org/10.1093/ije/29.4.722
- Martens EP, Pestman WR, de Boer A, Belitser SV, Klungel OH. Instrumental variables: Application and limitations. Epidemiology 2006; 17(3): 260-267 https://doi.org/10.1097/01.ede.0000215160.88317.cb
- Glymour MM. Natural Experiments and Instrumental Variable Analyses in Social Epidemiology. In: Oakes JM, Kaufman JS, editors. Methods for Social Epidemiology. San Francisco: Jossey-Bass; 2006. p. 429-460
- Zeliadt SB, Potosky AL, Penson DF, Etzioni R. Survival benefit associated with adjuvant androgen deprivation therapy combined with radiotherapy for high- and low-risk patients with nonmetastatic prostate cancer. Int J Radiat Oncol Biol Phys 2006; 66(2): 395-402 https://doi.org/10.1016/j.ijrobp.2006.04.048
- Brooks JM, Chrischilles EA, Scott SD, Chen-Hardee SS. Was breast conserving surgery underutilized for early stage breast cancer? Instrumental variables evidence for stage II patients from Iowa. Health Serv Res 2003; 38(6): 1385-1402 https://doi.org/10.1111/j.1475-6773.2003.00184.x
- Earle CC, Tsai JS, Gelber RD, Weinstein MC, Neumann PJ, Weeks JC. Effectiveness of chemotherapy for advanced lung cancer in the elderly: Instrumental variable and propensity analysis. J Clin Oncol 2001; 19(4): 1064-1070 https://doi.org/10.1200/JCO.2001.19.4.1064
- Hadley J, Polsky D, Mandelblatt JS, Mitchell JM, Weeks JC, Wang Q, Hwang YT. An exploratory instrumental variable analysis of the outcomes of localized breast cancer treatments in a Medicare population. Health Econ 2003; 12(3): 171-186 https://doi.org/10.1002/hec.710
- Bao Y, Duan N, Fox SA. Is some provider advice on smoking cessation better than no advice? An instrumental variable analysis of the 2001 National Health Interview Survey. Health Serv Res 2006; 41(6): 2114-2135 https://doi.org/10.1111/j.1475-6773.2006.00592.x
- Schwartz M, Ash AS. Estimating the effect of an intervention from observational data. In: lezzoni LI, editor. Risk Adjustment For Measuring Health Care Outcomes. 3rd ed. Aun Arbor: AcademyHealth/Health Administration Press; 2003
- Landrum MB, Ayanian JZ. Causal effect of ambulatory specialty care on mortality following myocardial infarction: A comparison of propensity score and instrumental variable analyses. Health Serv Outcome Res Meth 2001; 2(3-4) : 221-245 https://doi.org/10.1023/A:1020367111374
- Posner MA, Ash AS, Freund KM, Moskowitz MA, Shwartz M. Comparing standard regression, propensity score matching, and instrumental variables methods for determining the influence of mammography on stage of diagnosis. Health Serv Outcome Res Meth 2001; 2(3-4): 279-290 https://doi.org/10.1023/A:1020323429121
- Stukel TA, Fisher ES, Wennberg DE, Alter DA, Gottlieb DJ, Vermeulen MJ. Analysis of observational studies in the presence of treatment selection bias: Effects of invasive cardiac management on AMI survival using propensity score and instrumental variable methods. JAMA 2007; 297(3): 278-285 https://doi.org/10.1001/jama.297.3.278
- Yoon T, Hwang I, Sohn H, Koh K, Jeong B. The determinants of private health insurance purchasing decisions under national health insurance system in Korea. Kor J Health Pol Admin 2005; 15(4): 161-175 (Korean) https://doi.org/10.4332/KJHPA.2005.15.4.161
- Kang SW, Kwon YD, You CH. Effects of supplemental insurance on health care utilization and expenditures among cancer patients in Korea. Kor J Health Pol Admin 2005; 15(4): 65-80 (Korean) https://doi.org/10.4332/KJHPA.2005.15.4.065
- Lim JH, Kim SG, Lee EM, Bae SY, Park JH, Choi KS, Hahm MI, Park EC. The determinants of purchasing private health insurance in Korean cancer patients. J Prev Med Public Health 2007; 40(2) : 150-154 (Korean) https://doi.org/10.3961/jpmph.2007.40.2.150
- Korea Labor Institute. Korean Labor and Income Panel Study (KLIPS) User's Guide. Korea Labor Institute; 2006 (Korean)
- Rubin DB. Estimating causal effects from large data sets using propensity scores. Ann Intern Med 1997; 127(8 Pt 2): 757-763 https://doi.org/10.7326/0003-4819-127-8_Part_2-199710151-00064
-
Parsons LS. Performing a 1:N case-control match on propensity score. Proceedings of the Twenty-Ninth Aunual SAS
${\circledR}$ Users Group International Conference. Montreal: SAS Institute Inc.; 2004 - Greene WH. Econometric Analysis. 5th ed. Upper Saddle River: Prentice Hall; 2003
- Smith JA, Todd PE. Does matching overcome LaLonde's critique of nonexperimental estimators? J Econom 2005; 125(1-2) : 305-353 https://doi.org/10.1016/j.jeconom.2004.04.011
- Shah BR, Laupacis A, Hux JE, Austin PC. Propensity score methods gave similar results to traditional regression modeling in observational studies: A systematic review. J Clin Epidemiol 2005; 58(6): 550-559 https://doi.org/10.1016/j.jclinepi.2004.10.016
- Angrist JD, Krueger AB. Instrumental variables and the search for identification: From supply and demand to natural experiment. J Econ Persp 2001; 15(1): 69-85