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Generalised linear modelling for proportion data and standard linear modelling showed significant overdispersion and heteroscedasticity, respectively.
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The predicted quadratic model showed significant behaviour at a 95%% confidence level (P < 0.05).
All regression models showed significant increases in δ13C values during the experimental period.
Both models showed significant correlation between experimental and predicted data for all quality attributes.
Smoking models showed significant interaction effects between race and education for non-Latino Whites only.
For effects on terrestrial carbon storage, all models showed significant decreases in carbon stock in the two RCP scenarios.
Development of a polynomial model showed significant results for optimizing biosorption conditions for the RO 13 dye.
Hierarchical linear models showed significant group differences at T2 in knowledge, and these levels were maintained at T3.
When benign prostate hyperplasia was chosen as controls, both TT versus CC and recessive model showed significant difference.
We applied two-stage ETAS models to seismic activity data for the subregions where the stationary ETAS model showed significant misfits.
Recessive, overdominant and codominant models showed significant values, but the overdominant model was the best fitting our data according to AIC and BIC.
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