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Model selection follows the proposal of Verbeke and Molenberghs [ 18].
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ANN training and model selection followed the same protocol as above, except that only 150 pairs of test and training data were formed and, no additional validation data was available to prune networks that showed poor generalization.
Model selection followed the methodology proposed by Zuur et al. [49].
DNA model selection followed the procedure outlined by Posada and Buckley [ 81] as implemented in ModelTest v3.6 [ 82].
This requires more rigorous, iterative methods of feature and model selection, followed by cross-validations and external validations.
A selection follows.
A 2-step analysis strategy was used: marker selection, followed by model building.
Using the cell line data, we perform feature selection followed by model fitting, thus forming classifiers for dacetuzumab sensitivity or ER status.
Venn diagrams are based on the gplots R package version 2.11.0.1 (http://CRAN.R-project.org/package=gplots). Due to the polygenic nature of EAE, we used a multiple-QTL model, i.e. forward selection followed by backward elimination in R/qtl version 1.14 (93), to identify EAE QTLs in 421 BC rats, encompassing 150 rats used for eQTL analysis (Supplementary Material, Table S5).
In models fitted using univariate variable selection followed by multiple regression, relaxing the significance threshold for inclusion of a SNP in the model quickly led to more SNPs reaching the threshold than there are observations in the data.
This leads to the logical demand that future research studies in fracture management be conducted only by surgeons with appropriate surgical and research training in relevant animal models, and capabilities to discern model differences for model selection and follow-through.
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