Invited review: Use of meta-analysis in animal health and reproduction: Methods and applications
Notice bibliographique
Résumé
The objectives of this paper are to provide an introduction to meta-analysis and systematic review and to discuss the rationale for this type of research and other general considerations. We highlight methods used to produce a rigorous meta-analysis and discuss some aspects of interpretation of meta-analysis drawing on examples from the animal and veterinary science literature. Meta-analysis is a rapidly expanding area of research that has been relatively underutilized in animal and veterinary science. It is a quantitative, formal, epidemiological study design used to systematically assess previous research studies to derive conclusions about that body of research. Outcomes from a meta-analysis may include a more precise estimate of the effect of treatment or risk factor for disease, or other outcomes, than any individual study contributing to the pooled analysis. The examination of variability or heterogeneity in study results is also a critical outcome. The benefits of meta-analysis include a consolidated and quantitative review of a large, and often complex, sometimes apparently conflicting, body of literature. Meta-analytic methods place less emphasis on dichotomous outcomes from null hypothesis significance testing and greater emphasis on determining the magnitude and the precision of an effect of interest. A substantial benefit of meta-analysis is the potential to investigate new hypotheses using existing data, both through the development of a priori hypotheses and by examination of the heterogeneity in study responses. The specification of the outcome and hypotheses that are tested is critical to the conduct of meta-analyses, as is a sensitive literature search. A failure to identify the majority of existing studies can lead to erroneous conclusions; however, there are methods of examining data to identify the potential for studies to be missing; for example, by the use of funnel plots. Many of the statistical methods to conduct meta-analysis are widely used. Bayesian methods are well suited to meta-analysis. The post-hoc methods used to evaluate heterogeneity and publication bias, which include the I (2) statistic, L'Abbé plots, Galbraith plots, Rosenthal's N, and influential study analysis are exclusively used in meta-analysis. Examples where meta-analyses have been repeated in animal science or veterinary medicine show good consistency in estimates of effect. Findings of studies to date have provided new understandings of rumen modifiers, milk fever, parasite control, mastitis, somatotropin, and reproductive manipulations. Rigorously conducted meta-analyses are useful tools to improve animal well-being and productivity. The need to integrate findings from many studies ensures that meta-analytic research is desirable and the large body of research now generated makes the conduct of this research feasible.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».