PropertyValue
nif:beginIndex
  • 0 (xsd:integer)
nif:broaderContext
nif:endIndex
  • 646 (xsd:integer)
nif:isString
  • The process is summarized as: (1) the data are standardized such that each variable has mean 0 and norm 1; (2) a grid search of two tuning parameters associated with each penalty function is applied to the model (one for the fixed effects and one for the random effects), which control the strength of the shrinkage; (3) the model that gives a minimum Bayesian Information Criteria [47] is chosen as the optimal model that gives the best balance of fit and parsimony; and (4) the model is refit with only the selected fixed and random effects, with no constraints applied to the coefficients, using PROC GLIMMIX in SAS (SAS Institute, Carey, NC).
is nif:referenceContext of
rdf:type