<p>Models in bold were used for coefficient averaging.</p><p>The corrected Akaike information criterion (AICc) was used to rank the models using the difference with the lowest observed AICc (e.g., ΔAICc).</p><p>Akaike weights represent the probability that a given model best reduced the information loss for the observed data.</p><p>T, Ambient temperature; P Total body lipid (%); L, Location; A, Age; S, Sex.</p
<p>K = number of parameters used.</p><p>Delta AICc = difference between lowest AICc model and model ...
<p>K is the number of estimated parameters in the model; AIC<sub>c</sub> is the second order (due to...
<p><u>Df</u> = Degrees of freedom of each model; <u>lnLik</u> = Natural logarithm of Maximum Likelih...
<p>Model averaging based on corrected Akaike Information Criterion (AICc) weight (Wt).</p
<p>Models selected by various statistical methods. Columns are individual response variables. All mo...
<p>AIC<sub>c</sub> is Akaike’s information criterion corrected for small sample size, δAIC<sub>c</su...
<p>K = number of model parameters fitted to data, n = number of experimental observations (22 observ...
<p>Best models according to Akaike Information Criterion corrected for small sample bias (AICc).</p
<p>AICc: Akaike's Information Criterion corrected for small sample size; ΔAICc: variation in AICc re...
<p>The models (cumulative Akaike weight < 0.95) used in the model averaging techniques appear in nor...
Each model shows the determinant coefficient (R2), the Akaike’s Information Criterion (AIC) score, t...
Models were compared by means of the Akaike information criterion (AIC). Each value represents the a...
<p>Log-likelihood ln(L), Akaike information criterion corrected for sample size (AICc), difference i...
<p>The response variable used was number of fledglings. Data set indicates whether the data refer to...
<p>For each model, the sample-size adjusted AIC (AICc), Akaike differences (ΔAIC), Akaike weights (w...
<p>K = number of parameters used.</p><p>Delta AICc = difference between lowest AICc model and model ...
<p>K is the number of estimated parameters in the model; AIC<sub>c</sub> is the second order (due to...
<p><u>Df</u> = Degrees of freedom of each model; <u>lnLik</u> = Natural logarithm of Maximum Likelih...
<p>Model averaging based on corrected Akaike Information Criterion (AICc) weight (Wt).</p
<p>Models selected by various statistical methods. Columns are individual response variables. All mo...
<p>AIC<sub>c</sub> is Akaike’s information criterion corrected for small sample size, δAIC<sub>c</su...
<p>K = number of model parameters fitted to data, n = number of experimental observations (22 observ...
<p>Best models according to Akaike Information Criterion corrected for small sample bias (AICc).</p
<p>AICc: Akaike's Information Criterion corrected for small sample size; ΔAICc: variation in AICc re...
<p>The models (cumulative Akaike weight < 0.95) used in the model averaging techniques appear in nor...
Each model shows the determinant coefficient (R2), the Akaike’s Information Criterion (AIC) score, t...
Models were compared by means of the Akaike information criterion (AIC). Each value represents the a...
<p>Log-likelihood ln(L), Akaike information criterion corrected for sample size (AICc), difference i...
<p>The response variable used was number of fledglings. Data set indicates whether the data refer to...
<p>For each model, the sample-size adjusted AIC (AICc), Akaike differences (ΔAIC), Akaike weights (w...
<p>K = number of parameters used.</p><p>Delta AICc = difference between lowest AICc model and model ...
<p>K is the number of estimated parameters in the model; AIC<sub>c</sub> is the second order (due to...
<p><u>Df</u> = Degrees of freedom of each model; <u>lnLik</u> = Natural logarithm of Maximum Likelih...