backVarElimination.Res: NeRI-based backwards variable elimination

Description Usage Arguments Details Value Author(s) See Also

Description

This function removes model terms that do not significantly improve the "net residual" (NeRI)

Usage

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	backVarElimination_Res(object,
	                       pvalue = 0.05,
	                       Outcome = "Class",
	                       data,
	                       startOffset = 0, 
	                       type = c("LOGIT", "LM", "COX"),
	                       testType = c("Binomial", "Wilcox", "tStudent", "Ftest"),
	                       setIntersect = 1
						   )

Arguments

object

An object of class lm, glm, or coxph containing the model to be analyzed

pvalue

The maximum p-value, associated to the NeRI, allowed for a term in the model

Outcome

The name of the column in data that stores the variable to be predicted by the model

data

A data frame where all variables are stored in different columns

startOffset

Only terms whose position in the model is larger than the startOffset are candidates to be removed

type

Fit type: Logistic ("LOGIT"), linear ("LM"), or Cox proportional hazards ("COX")

testType

Type of non-parametric test to be evaluated by the improvedResiduals function: Binomial test ("Binomial"), Wilcoxon rank-sum test ("Wilcox"), Student's t-test ("tStudent"), or F-test ("Ftest")

setIntersect

The intersect of the model (To force a zero intersect, set this value to 0)

Details

For each model term x_i, the residuals are computed for the Full model and the reduced model( where the term x_i removed). The term whose removal results in the smallest drop in residuals improvement is selected. The hypothesis: the term improves residuals is tested by checking the pvalue of improvement. If p(residuals better than reduced residuals)>pvalue, then the term is removed. In other words, only model terms that significantly aid in improving residuals are kept. The procedure is repeated until no term fulfils the removal criterion. The p-values of improvement can be computed via a sign-test (Binomial) a paired Wilcoxon test, paired t-test or f-test. The first three tests compare the absolute values of the residuals, while the f-test test if the variance of the residuals is improved significantly.

Value

back.model

An object of the same class as object containing the reduced model

loops

The number of loops it took for the model to stabilize

reclas.info

A list with the NeRI statistics of the reduced model, as given by the getVar.Res function

back.formula

An object of class formula with the formula used to fit the reduced model

lastRemoved

The name of the last term that was removed (-1 if all terms were removed)

at.opt.model

the model with before the FSR procedure.

beforeFSC.formula

the string formula of the the FSR procedure

Author(s)

Jose G. Tamez-Pena and Antonio Martinez-Torteya

See Also

backVarElimination_Bin, bootstrapVarElimination_Bin bootstrapVarElimination_Res


FRESA.CAD documentation built on Jan. 13, 2021, 3:39 p.m.