Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Epidemioloģisks pārskata pētījums ar saskaņošanu× | Saskaņots gadījuma kontroles pētījums× | |
|---|---|---|
| Nozare | Epidemioloģija | Epidemioloģija |
| Saime | Process / pipeline | Process / pipeline |
| Izcelsmes gads≠ | Mid-to-late 20th century (formalized ~1970s–1990s) | 1950s–1970s |
| Autors≠ | Developed within the tradition of observational epidemiology; matching principles codified by Greenland, Rothman, and Kelsey in modern epidemiology texts | Brian MacMahon and others; systematised by Schlesselman (1982) |
| Tips≠ | Observational epidemiological study design | Observational analytic design |
| Pirmavots | Rothman, K. J., Greenland, S., & Lash, T. L. (2008). Modern Epidemiology (3rd ed.). Lippincott Williams & Wilkins. ISBN: 978-0781755641 | Rothman, K. J., Greenland, S., & Lash, T. L. (2008). Modern Epidemiology (3rd ed.). Lippincott Williams & Wilkins. ISBN: 978-0781755474 |
| Citi nosaukumi | matched cross-sectional survey, matched prevalence study, matched cross-sectional design, frequency-matched cross-sectional study | matched case-referent study, individually matched case-control, pair-matched case-control, matched case-control design |
| Saistītās | 5 | 5 |
| Kopsavilkums≠ | 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 matched case-control study is an observational epidemiological design in which each case (a person with the disease or outcome of interest) is paired with one or more controls (persons without the outcome) who share one or more characteristics — such as age, sex, or clinical setting — to control confounding. Exposure history is then compared between cases and their matched controls to estimate the odds ratio of the exposure-disease association. |
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