Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Utafiti wa Kikundi Kilinganishwa× | Utafiti wa Kikundi cha Wanafunzi wanaotarajiwa× | |
|---|---|---|
| Nyanja | Epidemiolojia | Epidemiolojia |
| Familia | Process / pipeline | Process / pipeline |
| Mwaka wa asili≠ | Mid-20th century; propensity-score variant 1983 | 1950s (systematic application); conceptual roots earlier |
| Mwanzilishi≠ | Established practice; propensity-score matching formalized by Rosenbaum & Rubin (1983) | Richard Doll and Austin Bradford Hill (landmark application, 1951-1954); cohort methodology formalised by modern epidemiology textbooks |
| Aina≠ | Observational analytic study design | Observational longitudinal study design |
| Chanzo asilia | 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: 978-0781755641 |
| Majina mbadala | matched follow-up study, paired cohort study, propensity-matched cohort, matched prospective study | longitudinal cohort study, prospective follow-up study, incidence study, prospective observational cohort |
| Zinazohusiana≠ | 5 | 6 |
| Muhtasari≠ | A matched cohort study is an observational design in which each exposed participant is paired with one or more unexposed counterparts who share key characteristics — such as age, sex, or comorbidity status — before both groups are followed forward in time to compare incident outcomes. Matching controls for measured confounders at the design stage, reducing bias that would otherwise require statistical adjustment alone. | A prospective cohort study assembles a group of participants who are free of the outcome of interest at baseline, measures their exposures, and then follows them forward in time to record who develops the outcome. By collecting exposure data before outcomes occur, it establishes a clear temporal sequence that supports causal inference — a major advantage over retrospective designs. It is the cornerstone observational method in epidemiology and clinical research. |
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