Table 3 shows the results of the statistical modeling and likelihood ratio tests for the reported parameters.
An algorithm for selecting the most likely kinetic structures, starting from the simplest models in the decision graphs, is developed based on the concepts of nested models and likelihood ratio tests.
For each data set, DS1, DS2, DS3, DS4, and DS5, there were three quantification methods investigated (1, 2, and L denote one-tissue compartment model, two-tissue compartment model, and likelihood estimation in graphical analysis, respectively).
For multivariate analysis, multiple logistic regression, fixed model and likelihood ratio method analyses were performed to ascertain the impact of different variables on the IPR-AASTRE-B and with the aim of adjusting for possible confounding effects.
Information regarding size, level of variability, molecular evolutionary models, and likelihood values from phylogenetic analyses for all mtDNA and nDNA genes can be found in Table 1.
This methodology implements a generalized least squares (GLS) model and likelihood ratio tests to resolve whether correlation between two characters is dependent on the underlying phylogeny [31], [32].
Tests for interactions were performed using Wald tests that include main effects and interaction terms in the model, and likelihood ratio testing, comparing the fit of the model with only main effects to the fit of the model with both main effects and interaction terms.
Results for the models and likelihood ratio tests are given in Table 3.
Outcome analysis will be performed using a Cox proportional hazards model and likelihood ratio test.
Analysis was conducted using multiple linear regression models and likelihood ratio tests.
