השוואת שיטות
סקרו את השיטות שבחרתם זו לצד זו; שורות שבהן יש הבדל מודגשות.
| תכנון ניסוי אדפטיבי× | מחקר אקולוגי× | |
|---|---|---|
| תחום≠ | מחקר קליני | אפידמיולוגיה |
| משפחה | Process / pipeline | Process / pipeline |
| שנת המקור≠ | 1990s-2000s | 19th century (Snow 1854); formalised mid-20th century |
| הוגה השיטה≠ | Stephen Pocock, Christopher Jennison, and statistical methodologists; FDA formalized guidance 2019 | Various; foundational work by John Snow (1854) and systematised in modern form by Brian MacMahon and colleagues |
| סוג≠ | Research Design | Observational epidemiological study |
| מקור מכונן≠ | Pocock, S. J. (2005). Current issues in the design and interpretation of clinical trials. BMJ, 330(7500), 1118–1121. link ↗ | Morgenstern, H. (1995). Ecologic studies in epidemiology: concepts, principles, and methods. Annual Review of Public Health, 16(1), 61–81. DOI ↗ |
| כינויים≠ | adaptive trial, adaptive design, response-adaptive randomization, RAR | aggregate study, correlational study, ecological correlation study, population-level study |
| קשורות≠ | 1 | 5 |
| תקציר≠ | An adaptive trial design allows pre-specified modifications to the trial based on interim data—such as sample size re-estimation, stopping for futility or efficacy, dropping ineffective arms, or shifting randomization ratios toward better-performing treatments. Developed systematically in the 1990s–2000s by statisticians like Pocock and Jennison, and formalized by the FDA in 2019, adaptive designs accelerate drug development, reduce exposure to ineffective treatments, and improve efficiency without inflating false-positive rates when properly executed. | An ecological study is an observational epidemiological design in which the unit of analysis is a group or population — a country, region, city, or time period — rather than an individual. Exposures and outcomes are measured as aggregates (rates, proportions, or means) and then correlated across groups to generate or evaluate hypotheses about population-level associations between risk factors and disease. |
| ScholarGateמערך נתונים ↗ |
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