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The variables described above were ranked according to the strength of their association with incident T2D by using the deviance from univariate logistic regression models.
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Parameters were estimated by MCMC methods [ 32] and the goodness of fit was evaluated using the deviance information criteria (DIC).
The scaling parameter was adjusted using the deviance method in each GEE.
The models were compared using the Deviance Information Criteria (DIC) [20].
Model fit was assessed using the deviance information criterion.
Regression trees are constructed using the "deviance" criterion.
We compared successive models using the deviance information criterion [ 22].
Model fitting was assessed using the deviance statistic.
26 We compared the fits of the models using the deviance information criterion (DIC).
The SEM was compared with the multi-trait model using the deviance information criterion (DIC) [ 24].
In addition, we assessed the goodness-of-fit of the model using the deviance.
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