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Which R2 should i use for model evaluation?Goodness of fit statistics (Variable Mortality (thous. heads)): Statistic Independent FullObservations 15 15Sum of weights 15.000 15.000DF 14 8-2 Log(Likelihood) 191.387 152.940R²(McFadden) 0.000 0.201R²(Cox and Snell) 0.000 0.923R²(Nagelkerke) 0.000 0.923AIC 193.387 166.940SBC 194.095 171.897Deviance 41.519 3.073Pearson Chi-square 56.158 3.089Iterations 0 6
You can use any of these pseudo R2 to measure how well the model is adjusted. R² (McFadden) is commonly used. However opinions vary in the statistical community about which one is considered as the best one.
Another important value to look at is the probability of Chi-square test on the log ratio. This is equivalent to the Fisher’s F test: we try to evaluate if the variables bring significant information by comparing the model as it is defined with a simpler model with only one constant.
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