Simulation Tests of Methods in Evolution, Ecology, and Systematics: Pitfalls, Progress, and Principles.
area under the curve
benchmark data sets
domain of applicability
equifinality
evaluation
validation
Journal
Annual review of ecology, evolution, and systematics
ISSN: 1543-592X
Titre abrégé: Annu Rev Ecol Evol Syst
Pays: United States
ID NLM: 101171971
Informations de publication
Date de publication:
Nov 2022
Nov 2022
Historique:
medline:
1
11
2022
pubmed:
1
11
2022
entrez:
18
12
2023
Statut:
ppublish
Résumé
Complex statistical methods are continuously developed across the fields of ecology, evolution, and systematics (EES). These fields, however, lack standardized principles for evaluating methods, which has led to high variability in the rigor with which methods are tested, a lack of clarity regarding their limitations, and the potential for misapplication. In this review, we illustrate the common pitfalls of method evaluations in EES, the advantages of testing methods with simulated data, and best practices for method evaluations. We highlight the difference between method evaluation and validation and review how simulations, when appropriately designed, can refine the domain in which a method can be reliably applied. We also discuss the strengths and limitations of different evaluation metrics. The potential for misapplication of methods would be greatly reduced if funding agencies, reviewers, and journals required principled method evaluation.
Identifiants
pubmed: 38107485
doi: 10.1146/annurev-ecolsys-102320-093722
pmc: PMC10723108
doi:
Types de publication
Journal Article
Langues
eng