Average Bayesian information criterion with s.e.m. across participants for all computational models considered and ordered by model fit. The number of parameters is displayed in parentheses. In line with the Akaike information criterion (see Fig 4 in the manuscript), ConfUnspec is the winning model. (TIF)</p
<p>For each model, the third column indicates the set of parameters assumed to vary across value con...
Within the framework of statistics, the goodness of statistical models is evaluated by criteria for ...
Selecting between competing structural equation models is a common problem. Often selection is based...
Models were compared by means of the Akaike information criterion (AIC). Each value represents the a...
<p>Bayesian Information Criterion (), summed across participants (<i>N</i> = 30) for the alternative...
Comparison of fitness of models based on Akaike information criterion (AIC) and Bayesian Information...
Note A. Contrasting AIC vs posterior probability calculated by Bayes-MMI for model selection and mul...
<p>Model parameter estimates and Akaike information criteria for best-fit models for each scenario.<...
<p>p<sub>C</sub>, prior common-source probability; σ<sub>P</sub>, standard deviation of the spatial ...
The widely applicable Bayesian information criterion (WBIC) is a simple and fast approximation to th...
BF10 = Bayes Factor (where 10 refers to the alternative hypothesis, H1, relative to the null hypothe...
<p>AICc: Akaike's Information Criterion corrected for small sample size; ΔAICc: variation in AICc re...
Frequencies of estimated via Bayesian information criterion over 50 simulated datasets with the sam...
BF10 = Bayes Factor (where 10 refers to the alternative hypothesis, H1, relative to the null hypothe...
<p>The probability of both the resources and host immunity models is high rather than the other hypo...
<p>For each model, the third column indicates the set of parameters assumed to vary across value con...
Within the framework of statistics, the goodness of statistical models is evaluated by criteria for ...
Selecting between competing structural equation models is a common problem. Often selection is based...
Models were compared by means of the Akaike information criterion (AIC). Each value represents the a...
<p>Bayesian Information Criterion (), summed across participants (<i>N</i> = 30) for the alternative...
Comparison of fitness of models based on Akaike information criterion (AIC) and Bayesian Information...
Note A. Contrasting AIC vs posterior probability calculated by Bayes-MMI for model selection and mul...
<p>Model parameter estimates and Akaike information criteria for best-fit models for each scenario.<...
<p>p<sub>C</sub>, prior common-source probability; σ<sub>P</sub>, standard deviation of the spatial ...
The widely applicable Bayesian information criterion (WBIC) is a simple and fast approximation to th...
BF10 = Bayes Factor (where 10 refers to the alternative hypothesis, H1, relative to the null hypothe...
<p>AICc: Akaike's Information Criterion corrected for small sample size; ΔAICc: variation in AICc re...
Frequencies of estimated via Bayesian information criterion over 50 simulated datasets with the sam...
BF10 = Bayes Factor (where 10 refers to the alternative hypothesis, H1, relative to the null hypothe...
<p>The probability of both the resources and host immunity models is high rather than the other hypo...
<p>For each model, the third column indicates the set of parameters assumed to vary across value con...
Within the framework of statistics, the goodness of statistical models is evaluated by criteria for ...
Selecting between competing structural equation models is a common problem. Often selection is based...