Other approaches, such as F-test for nested linear models, multiple regression model selection, using Akaike or Bayesian Information Criterion, bootstrapping analysis, also indicated IL-11 and/or IL-1β as the best predictor(s) of TB progression (i.e., weight loss) in gaining and moderately wasting F2 mice (Files S2, S3, S4, Table S1).
We propose two simple LOD-type statistics that integrate the information across time points and extend them, using the approach of Broman and Speed (2002), for multiple-QTL model selection.
A modeling approach (i.e., using multiple model construction and model selection approaches) can be a powerful tool for identifying selection on specific functional sequence groups by comparing the frequency and distribution of polymorphisms.
We think that our modeling approach (i.e., using multiple model construction and model selection approaches) can be a powerful tool for identifying selection on specific functional sequence groups by comparing the frequency and distribution of polymorphisms.
In this case, multiple iterations of the model selection procedure are performed by varying the splitting of data over the training, validation, and test sets [4].
Logistic regression models were built using the multiple fractional polynomial (MFP) model selection procedures available in the MFP package (Royston and Altman, 1994), following the fractional polynomial model selection procedures using each protein individually.
We fitted multiple predictor models using automated model selection via information theoretic approaches and multi-model averaging using maximum likelihood.
Multiple phases were required for model selection and development.
Second, model selection in multiple regression involving both fixed and random factors is not well understood; it is still largely unknown how best to conduct model selection in mixed effects models (e.g., whether AICC, BIC or other information criteria are best suited).
The author uses AICs to measure the quality of model selection, but multiple models seem to fit the data equally well.
