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This interaction reduced deviance and AIC and thus improved the model fit to the data.
The interacting model reduced deviance and AIC and thus improved the model fit to the data.
This stepwise reduction process was applied until the least complex model was identified that significantly reduced deviance in comparison with the next more complex model.
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Splitting stops when the cases in a subset are either entirely, or almost entirely, of the same class or the same value, or when further splitting does not improve discrimination between cases (i.e. does not substantially reduce deviance).
Our Risk Difference Model allows for the initial risk difference between the intervention groups and control groups and reduced the deviance from 23.54 in the Simple Model to 18.5, and thereby achieved the smallest deviance measure among all six models (ΔDev = 5.04, Δdf = 1, p = 0.02).
(iii) Variables with dichotomized P values>0.3 were added to the model, one by one, and any variable that reduced the deviance significantly was retained in the model.
The addition of the prognostic score to grade reduced residual deviance with a X1 = 5.39, p = 0.02.
Reported statistics for the smoother include the estimated degrees of freedom (edf) and result of F- test of whether the smoothed function significantly reduced model deviance.
The decision-tree algorithm divides the data to reduce the deviance, and classifies them into the pre-defined categories as many tree branches.
This model can be written as follows: logit (FPC ) = 0.61 + 0.68 log (CPR ) + 3.57 CP R 2 Compared to the simpler linear model, this alternative is better both in terms of reducing the deviance (p=0.028) and visually (Fig. 2).
Next, we set sensitivity parameters to be 1 and fit for the systematic negative error parameters (Systematic Error Model in Additional File 2) to test their effect on reducing the deviance.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com