방법 비교

	Matched Cross-Sectional Epidemiological Study	사례-대조 연구
분야	역학	역학
계열	Process / pipeline	Process / pipeline
기원 연도	Mid-to-late 20th century (formalized ~1970s–1990s)	1950s (formal methodology); precursors in the 1920s
창시자	Developed within the tradition of observational epidemiology; matching principles codified by Greenland, Rothman, and Kelsey in modern epidemiology texts	Janet Lane-Claypon (early precursors, 1926); formalized by Brian MacMahon and Jerome Cornfield in the 1950s–1960s
유형	Observational epidemiological study design	Observational analytic study design
원전	Rothman, K. J., Greenland, S., & Lash, T. L. (2008). Modern Epidemiology (3rd ed.). Lippincott Williams & Wilkins. ISBN: 978-0781755641	Schlesselman, J.J. (1982). Case-Control Studies: Design, Conduct, Analysis. Oxford University Press. ISBN: 978-0195027860
별칭	matched cross-sectional survey, matched prevalence study, matched cross-sectional design, frequency-matched cross-sectional study	case-referent study, case-control design, retrospective case-control, case-control analysis
관련	5	6
요약	A matched cross-sectional epidemiological study is an observational design that measures exposure and outcome simultaneously in a population sample while applying matching to control for one or more confounding variables. By pairing or grouping participants on key characteristics such as age, sex, or socioeconomic status before or during analysis, the design reduces confounding bias without requiring longitudinal follow-up, making it efficient for estimating prevalence and cross-sectional associations.	A case-control study is a retrospective observational design in which individuals who have developed a disease or outcome of interest (cases) are compared with individuals who have not (controls) to determine whether prior exposure to a putative risk factor differs between the two groups. The primary measure of association is the odds ratio, which approximates the relative risk when the outcome is rare. Case-control studies are especially efficient for investigating rare diseases and generating etiological hypotheses.