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| Meta-anàlisi× | Biaix de publicació× | |
|---|---|---|
| Camp≠ | Escriptura acadèmica | Estadística per a la recerca |
| Família | Process / pipeline | Process / pipeline |
| Any d'origen≠ | 1976 | 1979 |
| Autor original≠ | Glass (1976, term coining); Fisher and Pearson (statistical foundations) | Robert Rosenthal |
| Tipus≠ | Document Type | Concept |
| Font seminal≠ | Page, M. J., et al. (2021). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ, 372, n71. DOI ↗ | Rosenthal, R. (1979). The file drawer problem and tolerance for null results. Psychological Bulletin, 86(3), 638–641. DOI ↗ |
| Àlies | quantitative synthesis, meta-synthesis, pooled analysis, statistical integration | file drawer problem, selective reporting, outcome reporting bias, funnel plot asymmetry |
| Relacionats≠ | 2 | 4 |
| Resum≠ | Meta-analysis is the statistical pooling of quantitative findings from multiple independent studies to produce a combined effect estimate. By aggregating data across studies, meta-analysis increases statistical power, reduces random error, and provides a precise summary of an intervention's effectiveness or an association's magnitude. Gene V. Glass coined the term in 1976, formalizing a technique that has become indispensable for evidence synthesis in medicine, psychology, education, and other evidence-based disciplines. | Publication bias occurs when the results of a study influence whether the study is published. Typically, studies with statistically significant or positive results are more likely to be published than studies with non-significant or negative results, even if both are scientifically valid. This bias distorts the published literature, making treatments appear more effective than they actually are. Rosenthal (1979) termed this the 'file drawer problem': research with null results sits in file drawers, unpublished, creating a biased sample of published evidence. Funnel plots and statistical tests (e.g., Egger test) can detect asymmetry suggesting publication bias; meta-analyses must account for this bias. |
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