A model capable of explaining 80% of the CSFT variability and a model capable of explaining more than 96% of the precipitate content variability were obtained using multiple regression analysis.
A fundamental model capable of explaining observed associations among variables might be suitable, potentially a latent variable model [ 10].
In order to evaluate the fit of a model, values of explained variation, R, and predicted variation, Q, were computed as in [ 51].
The simulations we describe have important implications for the ability of ecotype model to explain the divergence of sympatric lineages.
Overall this model of analysis explains some 14% of the variance.
We had previously tested the transtheoretical model (stages of change model) to explain barriers to behaviour change for mitigation [ 19].
For this model, the degree of explained variance was 0.899 and the RMSE was 1.746 m.
For each model, the proportion of explained variance was estimated.
The R of the model explaining the VAS score was 0.263 and the R of the model explaining EQ-5D utilities was 0.310.
The R of the model explaining the VAS scores was 0.290 and the R of the model explaining EQ-5D utilities was 0.322.
