Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Utafiti Linganishi wa Usahihi wa Utambuzi× | Utafiti wa Cohort× | |
|---|---|---|
| Nyanja | Epidemiolojia | Epidemiolojia |
| Familia | Process / pipeline | Process / pipeline |
| Mwaka wa asili≠ | 1990s–2000s (formalised with STARD 2003) | Mid-20th century (formal epidemiological design codified ~1950s) |
| Mwanzilishi≠ | Evolved from matched case-control methodology; STARD standards formalised by Bossuyt et al. (2003) | Doll & Hill (British Doctors Study, 1951); Snow (cholera, 1854) |
| Aina≠ | Diagnostic / clinical epidemiology study design | Observational longitudinal study design |
| Chanzo asilia≠ | Bossuyt, P. M., Reitsma, J. B., Bruns, D. E., Gatsonis, C. A., Glasziou, P. P., Irwig, L. M., Lijmer, J. G., Moher, D., Rennie, D., & de Vet, H. C. W. (2003). Towards complete and accurate reporting of studies of diagnostic accuracy: The STARD initiative. BMJ, 326(7379), 41–44. DOI ↗ | Rothman, K. J., Greenland, S., & Lash, T. L. (2008). Modern Epidemiology (3rd ed.). Lippincott Williams & Wilkins. ISBN: 978-0781755641 |
| Majina mbadala | matched DAS, paired diagnostic accuracy study, matched test accuracy study, matched sensitivity-specificity study | longitudinal study, follow-up study, panel study, incidence study |
| Zinazohusiana≠ | 4 | 6 |
| Muhtasari≠ | A matched diagnostic accuracy study evaluates how well an index test correctly identifies a target condition in study participants who have been matched on key characteristics — such as age, sex, or disease severity — to control for confounding. By pairing diseased and non-diseased subjects on relevant factors before administering the test, the design isolates the test's own discriminative performance from variation attributable to imbalanced covariates, yielding cleaner estimates of sensitivity, specificity, and related accuracy measures. | A cohort study assembles a group of individuals who share a common starting point — typically freedom from the outcome of interest — and follows them over time to observe who develops the outcome. By comparing incidence rates between exposed and unexposed subgroups, researchers can estimate relative risk and absolute risk differences. Cohort studies are the gold-standard observational design for measuring disease incidence and establishing temporal relationships between exposure and outcome. |
| ScholarGateSeti ya data ↗ |
|
|