Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Временной метаанализ× | Систематический обзор литературы× | |
|---|---|---|
| Область | Наукометрия | Наукометрия |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1992 (cumulative form); refined through 2000s | 1993 (Cochrane Collaboration); 2004 (Kitchenham SLR guidelines) |
| Автор метода≠ | Lau et al. (cumulative variant); Borenstein et al. (general meta-analytic framework) | Archie Cochrane (conceptual foundation); formalized by the Cochrane Collaboration (1993) and Barbara Kitchenham in software engineering (2004) |
| Тип≠ | Quantitative evidence synthesis variant | Evidence synthesis methodology |
| Основополагающий источник≠ | Borenstein, M., Hedges, L. V., Higgins, J. P. T., & Rothstein, H. R. (2009). Introduction to Meta-Analysis. Wiley. ISBN: 978-0470057247 | Kitchenham, B. (2004). Procedures for Performing Systematic Reviews. Keele University Technical Report TR/SE-0401. link ↗ |
| Другие названия | temporal meta-analysis, period-stratified meta-analysis, time-segmented meta-analysis, chronological meta-analysis | SLR, systematic review, evidence synthesis review, structured literature review |
| Связанные | 5 | 5 |
| Сводка≠ | Time-sliced meta-analysis is a variant of standard meta-analysis in which the primary studies are partitioned into successive time periods (slices) and a separate pooled effect estimate is computed for each period. By comparing pooled effects across periods, researchers can detect whether an intervention's effectiveness, a relationship's magnitude, or a methodological consensus has shifted over time. This temporal lens transforms a static evidence summary into a longitudinal narrative of how scientific knowledge on a topic has evolved. | A systematic literature review (SLR) is a structured, reproducible method for identifying, appraising, and synthesizing all relevant studies on a research question. Unlike a narrative review, it follows an explicit, pre-specified protocol — from database search strings through inclusion criteria to data extraction — so that the process is transparent, auditable, and replicable by other researchers. It is widely used in medicine, education, software engineering, and the social sciences to produce the most comprehensive possible evidence base on a topic. |
| ScholarGateНабор данных ↗ |
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