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To obtain confidence intervals (CIs) for our model selection statistic, we calculated nucleotide diversity for each of the 1,000 replicates and obtained the interval containing 95% of the realized nucleotide diversities.
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All resulting models were evaluated for how well the model fit the data using a quasi-log-likelihood under the independence model information criterion (QIC) statistic for model selection [ 20].
PALM results in an inference of phylogenetic relationship not only by vanquishing the computation difficulty of ML methods but also providing statistic methods for model selection and bootstrapping.
They incorporate this property in defining the test statistic for genetic model selection (ZGMS) and calculating the p value.
Based on the QIC statistic for GEE model selection, the explanatory variables of the final model were age, survey year, gender, SES group, denture-wearing, SDC during childhood, and the interaction between age and SDC during childhood (P < 0.05) (Table 2).
In this project, the QIC statistic was used for GEE model selection.
The -2 Log-Likelihood statistic and two commonly used penalized model selection criteria, the Bayesian information criterion (BIC) and Akaike's information criterion (AIC), were used for model comparison.
Separate results using the Akaike Information Criterion, another statistic that is commonly used to guide model selection, also reveal that model fit improves when the covariate list is expanded to include parental education.
Model selection was facilitated in QIF using a goodness-of-fit statistic.
Model selection was performed in a stepwise fashion using the R change statistic (Field, 2009).
Again, summary statistic selection is an important aspect of ABC's ability to provide adequate model selection capability.
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