Sentence examples for each models was calculated from inspiring English sources

OR estimation of each models was calculated by using the fixed-effects model (Mantel-Haenszel method) if the I ≤ 50% (which indicated a lack of heterogeneity) [ 17].

Power coefficient of each models are calculated and compared.

The root mean square error of prediction (RMSEP) for each model was calculated using {text{RMSEP}} = sqrt {frac{{mathop sum nolimits_{i = 1}^{n} (y_{i - } hat{y}_{i} )^{2} }}{n}},where y i is the measured and (hat{y}_{i}) is the predicted value.

The log-likelihood of each model was calculated as the sum of the log-likelihoods of their component functions.

This process was repeated 1000 times and the deviance of each model was calculated to determine whether the deviance of the observed model exceeded that of the simulated data.

Second, the cumulative Spearman rank correlation between sensitivity results generated using the ODE15s, BDF3 and FD methods for each model was calculated as a function of the number of parameter sets sampled.

Furthermore, the acceptance rate of each model was calculated.

The likelihood for each model was calculated with BayesDiscrete in the BayesTraits package [ 66], using the branch length estimates and character coding as above.

The area under the receiver operating characteristic (AROC) curve (c-statistic) for each model was calculated and used as the primary criterion upon which to judge a model's discriminative ability (10).

Once the ELS composition of each model was calculated the total number of units for each option in each model and the baseline were then multiplied by the average per annum costs per unit (See Table  7 in Appendix) using the costs from the SAFFIE (2007) and Nix (2010), following the establishment and management guidelines laid out in each option (Natural England 2010).

AICc for each model was calculated as AICc (model) = 2 k + n ln(RSS/ n) + [2 k (k + 1)/(n - k - 1)], where k is the number of free parameters (3 strains × parameters varied + parameters not varied + 1 variance parameter) and n is the total number of observations (18 rats × 8 target times - 16 empty cells = 128).