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The model with lower deviance information criterion (DIC) was preferred.
Lower deviance and AIC mean better fit to data.
Hence, a lower deviance indicates a higher likelihood and better fit to the data.
A model with lower deviance provides a better fit to the data and hence will be preferred.
For each outcome, fixed and random effects models were evaluated, and the better fitting model was selected based on the lower Deviance Information Criterion value [ 31].
Deviance is a measure of how well the statistical model describes the observed data, with a lower deviance implying a better fit (see Appendix for details).
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In comparing HC to FENNS-BL, lower G (deviance reduction 6.03 on 1 df, Pr χ2) = 0.01) indicated membership in the FENNS-BL group over the HC group.
The model with the offset has a lower global deviance then the model without the offset but the difference is not large.
In comparing HC to FENNS-4w, lower G levels (deviance reduction 17.32 on 1 df, Pr χ2) = 0.00003) indicated membership in the FENNS-4w group as opposed to the HC group.
†A lower or more negative deviance indicates better model fit.
Typically, models that had high adjusted deviance had lower AUC values based on independent data.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com