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| Meta-analisis Berbasis Protokol× | Tinjauan Literatur Sistematis× | |
|---|---|---|
| Bidang | Saintometrika | Saintometrika |
| Keluarga | Process / pipeline | Process / pipeline |
| Tahun asal≠ | 1990s–2015 (Cochrane established 1993; PROSPERO launched 2011; PRISMA-P 2015) | 1993 (Cochrane Collaboration); 2004 (Kitchenham SLR guidelines) |
| Pencetus≠ | Cochrane Collaboration; formalized through PROSPERO and PRISMA-P initiatives | Archie Cochrane (conceptual foundation); formalized by the Cochrane Collaboration (1993) and Barbara Kitchenham in software engineering (2004) |
| Tipe≠ | Evidence synthesis with pre-registered protocol | Evidence synthesis methodology |
| Sumber perintis≠ | Higgins, J. P. T., Thomas, J., Chandler, J., Cumpston, M., Li, T., Page, M. J., & Welch, V. A. (Eds.). (2023). Cochrane Handbook for Systematic Reviews of Interventions (Version 6.4). Cochrane. link ↗ | Kitchenham, B. (2004). Procedures for Performing Systematic Reviews. Keele University Technical Report TR/SE-0401. link ↗ |
| Alias | pre-registered meta-analysis, prospective meta-analysis, registered meta-analysis, protocol-driven meta-analysis | SLR, systematic review, evidence synthesis review, structured literature review |
| Terkait≠ | 4 | 5 |
| Ringkasan≠ | A protocol-based meta-analysis is a meta-analysis conducted according to a detailed, pre-registered protocol that specifies all key methodological decisions — research questions, eligibility criteria, search strategy, outcome measures, and statistical methods — before data collection begins. Pre-registration, typically through PROSPERO or a comparable registry, distinguishes this approach from post-hoc or exploratory meta-analyses and substantially reduces the risk of selective reporting and outcome switching. | 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. |
| ScholarGateSet data ↗ |
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