lrm_model | R Documentation |
Fit binary logistic regression models using MLE or penalized MLE. All the dependent variables are modeled using selected independent variables automatically. Multi-colliearity is removed in the final models using correlation analysis.
lrm_model(data = data, DVList = DVList, IDVList = IDVList, Included = NULL, all = FALSE, parallel = FALSE)
data |
The data. It must contain the variables (columns) that should be used, directly or indirectly, in the modelling procedures. Missing values (NA) are allowed. |
DVList |
Dependent variables list which are needed to be modelled. |
IDVList |
Independent variables list used to model dependent variables. |
Included |
A variable list whose elements are forced to be included in the models, no matter variable selection is conducted or not. Default: NULL. |
all |
Logical. If TRUE, the function will not do variables selection, only model fitting will be done. Default: FALSE. |
A list data structure which contains model results.
model.Psyco <- lrm_model(data=ModelBase.new, DVList=DVList, IDVList=PsycoVars)
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