Comparar métodos

	Desenho de Estudo de Caso-Controle	Desenho de Estudo de Coorte	Desenho de Estudo Transversal
Área	Pesquisa clínica	Pesquisa clínica	Pesquisa clínica
Família	Process / pipeline	Process / pipeline	Process / pipeline
Ano de origem	1950s-1970s	1970s-1980s	1950s-1970s
Autor original	Jerome L. Schlesselman, Brian MacMahon, Thomas Pugh	Donald Acheson, Olli Miettinen, and others in modern epidemiology	Epidemiologists in the mid-20th century; formalized by Kelsey, Rothman, and others
Tipo	Research Design	Research Design	Research Design
Fonte seminal	Schlesselman, J. J. (1982). Case-Control Studies: Design, Conduct, Analysis. Oxford University Press. ISBN: 978-0195027815	Miettinen, O. S. (1976). Estimability and estimation in case-referent studies. American Journal of Epidemiology, 103(2), 226–235.	Kelsey, J. L., Whittemore, A. S., Evans, A. S., & Thompson, W. D. (1996). Methods in Observational Epidemiology (2nd ed.). Oxford University Press. ISBN: 978-0195083299
Outros nomes	case-control study, retrospective study, matched case-control, nested case-control	prospective study, follow-up study, longitudinal study, cohort study	prevalence study, cross-sectional survey, snapshot study, survey design
Relacionados	2	2	2
Resumo	A case-control study identifies individuals with a disease or outcome (cases) and a comparison group without the outcome (controls), then measures prior exposure retrospectively. Developed in the 1950s–1970s by epidemiologists like Schlesselman and MacMahon, case-control studies are especially efficient for rare diseases, as they sample cases enriched for the outcome, avoiding the need for enormous cohorts. They are a mainstay of clinical epidemiology, observational research, and outbreak investigations.	A cohort study follows a group of individuals forward in time from exposure to outcome. Exposed and unexposed participants (or participants with differing exposure levels) are enrolled at baseline, characterized, and observed prospectively until the outcome occurs or the study ends. Cohort studies are fundamental to epidemiology and are the design of choice for establishing causal associations when randomized trials are infeasible or unethical.	A cross-sectional study (or prevalence study) measures exposure and outcome simultaneously at a single point in time, producing a 'snapshot' of a population. Respondents are recruited and surveyed (or examined) on the same occasion, capturing current prevalence of both exposure and disease. Cross-sectional studies are simple, quick, and inexpensive, making them popular for needs assessments, surveillance, and generating hypotheses—though they cannot establish causality due to lack of temporal sequence.