Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Метааналіз із розбиттям на часові зрізи× | Систематичний огляд літератури× | |
|---|---|---|
| Галузь | Наукометрія | Наукометрія |
| Родина | Process / pipeline | Process / pipeline |
| Рік появи≠ | 1992 (cumulative form); refined through 2000s | 1993 (Cochrane Collaboration); 2004 (Kitchenham SLR guidelines) |
| Автор методу≠ | 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 |
| Основоположне джерело≠ | 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 ↗ |
| Інші назви | temporal meta-analysis, period-stratified meta-analysis, time-segmented meta-analysis, chronological meta-analysis | SLR, systematic review, evidence synthesis review, structured literature review |
| Пов'язані | 5 | 5 |
| Підсумок≠ | 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. |
| ScholarGateНабір даних ↗ |
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