Sensitivity and specificity of information criteria
Abstract Information criteria (ICs) based on penalized likelihood, such as Akaike's
information criterion (AIC), the Bayesian information criterion (BIC) and sample-size …
information criterion (AIC), the Bayesian information criterion (BIC) and sample-size …
Sensitivity and specificity of information criteria.
JJ Dziak, DL Coffman, ST Lanza, R Li… - Briefings in …, 2020 - search.ebscohost.com
Abstract Information criteria (ICs) based on penalized likelihood, such as Akaike's
information criterion (AIC), the Bayesian information criterion (BIC) and sample-size …
information criterion (AIC), the Bayesian information criterion (BIC) and sample-size …
Sensitivity and specificity of information criteria
JJ Dziak, DL Coffman, ST Lanza, R Li - PeerJ PrePrints, 2017 - search.proquest.com
Choosing a model with too few parameters can involve making unrealistically simple
assumptions and lead to high bias, poor prediction, and missed opportunities for insight …
assumptions and lead to high bias, poor prediction, and missed opportunities for insight …
[PDF][PDF] Sensitivity and specificity of information criteria
JJ Dziak, DL Coffman, ST Lanza, R Li - 2012 - methodology.psu.edu
Choosing a model with too few parameters can involve making unrealistically simple
assumptions and lead to high bias, poor prediction, and missed opportunities for insight …
assumptions and lead to high bias, poor prediction, and missed opportunities for insight …
[PDF][PDF] Sensitivity and Specificity of Information Criteria
JJ Dziak, DL Coffman, ST Lanza, R Li, LS Jermiin - 2019 - scholar.archive.org
Abstract Information criteria (ICs) based on penalized likelihood, such as Akaike's
Information Criterion (AIC), the Bayesian Information Criterion (BIC), and samplesize …
Information Criterion (AIC), the Bayesian Information Criterion (BIC), and samplesize …
Sensitivity and Specificity of Information Criteria
JJ Dziak, DL Coffman, ST Lanza, R Li, LS Jermiin - bioRxiv, 2018 - biorxiv.org
Abstract Information criteria (ICs) based on penalized likelihood, such as Akaike's
Information Criterion (AIC), the Bayesian Information Criterion (BIC), and sample-size …
Information Criterion (AIC), the Bayesian Information Criterion (BIC), and sample-size …
Sensitivity and specificity of information criteria
JJ Dziak, DL Coffman, ST Lanza… - Briefings in …, 2020 - pubmed.ncbi.nlm.nih.gov
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 …
criterion (AIC), the Bayesian information criterion (BIC) and sample-size-adjusted versions of …
[PDF][PDF] Sensitivity and specificity of information criteria
JJ Dziak, DL Coffman, ST Lanza, R Li - 2012 - latentclassanalysis.com
Choosing a model with too few parameters can involve making unrealistically simple
assumptions and lead to high bias, poor prediction, and missed opportunities for insight …
assumptions and lead to high bias, poor prediction, and missed opportunities for insight …
[PDF][PDF] Sensitivity and specificity of information criteria
JJ Dziak, DL Coffman, ST Lanza, R Li - PeerJ PrePrints - peerj.com
Choosing a model with too few parameters can involve making unrealistically simple
assumptions and lead to high bias, poor prediction, and missed opportunities for insight …
assumptions and lead to high bias, poor prediction, and missed opportunities for insight …
[HTML][HTML] Sensitivity and specificity of information criteria
JJ Dziak, DL Coffman, ST Lanza, R Li… - Briefings in …, 2020 - ncbi.nlm.nih.gov
Abstract Information criteria (ICs) based on penalized likelihood, such as Akaike's
information criterion (AIC), the Bayesian information criterion (BIC) and sample-size …
information criterion (AIC), the Bayesian information criterion (BIC) and sample-size …