<p>AICc: Akaike's Information Criterion corrected for small sample size; ΔAICc: variation in AICc relative to the best-performing model; Likelihood: likelihood of the model, given the data; <i>wi</i>: Akaike weights; <i>K</i>: number of estimable parameters.</p
<p>Model parameter estimates and Akaike information criteria for best-fit models for each scenario.<...
The various debates around model selection paradigms are important, but in lieu of a consensus, ther...
<p>K is the number of estimated parameters in the model; AIC<sub>c</sub> is the second order (due to...
<p>AICc: Akaike's Information Criterion corrected for small sample size; ΔAICc: variation in AICc re...
<p>AICc: Akaike's Information Criterion corrected for small sample size; ΔAICc: variation in AICc re...
<p>AICc: Akaike's Information Criterion corrected for small sample size; ΔAICc: variation in AICc re...
<p>The response variable used was number of fledglings. Data set indicates whether the data refer to...
<p>Best models according to Akaike Information Criterion corrected for small sample bias (AICc).</p
Models were compared by means of the Akaike information criterion (AIC). Each value represents the a...
<p>The Akaike information criterion (AICc) values for regression models investigating the effects of...
<p>Models selected by various statistical methods. Columns are individual response variables. All mo...
<p>OR* (odds ratio).</p><p>AIC*(Akaike Information Criterion); The AIC is a measure of the relative ...
<p>AIC<sub>c</sub> is Akaike’s information criterion corrected for small sample size, δAIC<sub>c</su...
<p>The Akaike information criterion (AICc) values for regression models investigating the effects of...
<p>Table of Akaike Information Criterion (AIC) and Adjusted R<sup>2</sup> values for the different p...
<p>Model parameter estimates and Akaike information criteria for best-fit models for each scenario.<...
The various debates around model selection paradigms are important, but in lieu of a consensus, ther...
<p>K is the number of estimated parameters in the model; AIC<sub>c</sub> is the second order (due to...
<p>AICc: Akaike's Information Criterion corrected for small sample size; ΔAICc: variation in AICc re...
<p>AICc: Akaike's Information Criterion corrected for small sample size; ΔAICc: variation in AICc re...
<p>AICc: Akaike's Information Criterion corrected for small sample size; ΔAICc: variation in AICc re...
<p>The response variable used was number of fledglings. Data set indicates whether the data refer to...
<p>Best models according to Akaike Information Criterion corrected for small sample bias (AICc).</p
Models were compared by means of the Akaike information criterion (AIC). Each value represents the a...
<p>The Akaike information criterion (AICc) values for regression models investigating the effects of...
<p>Models selected by various statistical methods. Columns are individual response variables. All mo...
<p>OR* (odds ratio).</p><p>AIC*(Akaike Information Criterion); The AIC is a measure of the relative ...
<p>AIC<sub>c</sub> is Akaike’s information criterion corrected for small sample size, δAIC<sub>c</su...
<p>The Akaike information criterion (AICc) values for regression models investigating the effects of...
<p>Table of Akaike Information Criterion (AIC) and Adjusted R<sup>2</sup> values for the different p...
<p>Model parameter estimates and Akaike information criteria for best-fit models for each scenario.<...
The various debates around model selection paradigms are important, but in lieu of a consensus, ther...
<p>K is the number of estimated parameters in the model; AIC<sub>c</sub> is the second order (due to...