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A significantly lower deviance from a model with a lag time of k years means that using the smoothed pattern of residential locations from k years ago significantly explains overall NHL risk.
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Lower deviance and AIC mean better fit to data.
The model with lower deviance information criterion (DIC) was preferred.
Hence, a lower deviance indicates a higher likelihood and better fit to the data.
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).
A model with lower deviance provides a better fit to the data and hence will be preferred.
Predictions of the ERC based on a natural spline model and a linear model are presented in Figure 2. The lower deviance of the natural spline (deviance = 25.84, 27 df) compared with that of the linear model (deviance = 29.25, 28 df) suggests a slightly better fit [chi square test (1 df), p = 0.06].
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].
Probability involves possible deviance from trajectories established from past facts and their distribution.
These specifications are normally expressed as a target or "center"; deviance from the center is permitted within a specified range.
"We look for positive deviance from families we think are very typical," explained Lim Miller.
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