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Data were analysed using generalised estimation equation (GEE) modelling.
Data were analysed using generalised linear mixed-effects models separately for horned and hornless goats.
Fourteen samples were selected for free choice profiling and analysed using generalised procrustes analysis (GPA).
To account for clustering, we analysed data using generalised estimating equations.
Foetal weights and crown-rump lengths were recorded and analysed using generalised linear model (GLM) procedures.
Using generalised estimating equations, neighbourhood obesogenicity was not associated with BMI in the overall sample.
The weights between the hidden and output layers are determined in a one-step regression type approach using generalised inverse.
Stem lesion length was modelled using generalised least-squares models fitted by restricted maximum likelihood (Pinheiro et al. 2014).
The model was estimated using generalised least squares (GLS), which also yields the variances of both error terms.
The dynamic analysis was resolved using generalised properties of the building and numerical methods that are valid for sdof systems.
The remaining parameters included in the model were selected using generalised cross validation (GCV) [31].
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