Sensitivity and specificity of information criteria

Volume: 21, Issue: 2, Pages: 553 - 565
Published: Mar 20, 2019
Abstract
Information criteria (ICs) based on penalized likelihood, such as Akaike's information criterion (AIC), the Bayesian information criterion (BIC) and sample-size-adjusted versions of them, are widely used for model selection in health and biological research. However, different criteria sometimes support different models, leading to discussions about which is the most trustworthy. Some researchers and fields of study habitually use one or the...
Paper Details
Title
Sensitivity and specificity of information criteria
Published Date
Mar 20, 2019
Volume
21
Issue
2
Pages
553 - 565
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.