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A pseudo-R 2 compares the likelihood for the intercept-only model to the likelihood for the model with predictors, and returns an indication on the strength of the model.
Logistic regression analysis was performed to quantify the net effect of hypothermia on admission to the ICU on 28-day mortality and to develop a model with predictors.
Backward selection was used to establish the most parsimonious model, with predictors significant at the α = 0.05 level (Table 3, base model).
The predictive model explained 51.3% of the variation in EVGGFP (AIC = 3123.8, BIC = 3206.8 for model with predictors compared to AIC = 3883.1, BIC = 3894.9 for the null model).
Because Item Response Theory model with predictors are very computer intensive and individual models may take over 24 hours to run in personal computers, a special arrangement of the operating system was instituted to obtain maximal performance.
At first, all potential predictors of each subsets (clinical or radiological) were entered into the regression model through 'forward selection' and the resulting model with predictors having only statistical significant effects were noted.
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Let (reg) be a regression model with predictor variables (v_{1}, v_{i}, ldots, v_{n}).
However, baseline PAEE accounted for most of the variance in each model, with predictor variables typically adding less than 1% to the explained variance.
We analysed the results from both pedigrees simultaneously using a model with predictor variables added in the order block, autosomal inbreeding and X-chromosome inbreeding.
Multiple stepwise regression analysis converged the best-fit models with predictors from meteorological conditions and the proximity to specific point, area, and mobile sources on the residential outdoor VOC concentrations.
In the first-level GLM, conditions were modeled with predictors comprising 20-second duration boxcars convolved with the default hemodynamic response function (HRF) of SPM5.
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