filter: Filter function for predictive/prognostic biomarker...

In SubgrpID: Patient Subgroup Identification for Clinical Drug Development

Description

Filter function for Prognostic and preditive biomarker signature development for Exploratory Subgroup Identification in Randomized Clinical Trials

Usage

filter(data,
type="c",
yvar,
xvars,
censorvar=NULL,
trtvar=NULL,
trtref=1,
n.boot=50,
cv.iter=20,
pre.filter=length(xvars),
filter.method=NULL)

Arguments

data	input data frame
type	type of response variable: "c" continuous; "s" survival; "b" binary
yvar	variable (column) name for response variable
xvars	vector of variable names for predictors (covariates)
censorvar	variable name for censoring (1: event; 0: censor), default = NULL
trtvar	variable name for treatment variable, default = NULL (prognostic signature)
trtref	coding (in the column of trtvar) for treatment arm, default = 1 (no use for prognostic signature)
n.boot	number of bootstrap for the BATTing procedure
cv.iter	Algotithm terminates after cv.iter successful iterations of cross-validation, or after max.iter total iterations, whichever occurs first
pre.filter	NULL (default), no prefiltering conducted;"opt", optimized number of predictors selected; An integer: min(opt, integer) of predictors selected
filter.method	NULL (default), no prefiltering; "univariate", univaraite filtering; "glmnet", glmnet filtering

Details

The function contains two algorithms for filtering high-dimentional multivariate (prognostic/predictive) biomarker candidates via univariate fitering (used p-values of group difference for prognostic case, p-values of interaction term for predictive case); LASSO/Elastic Net method. (Tian L. et al 2012)

Value

var	a vector of filter results of variable names

References

Tian L, Alizadeh A, Gentles A, Tibshirani R (2012) A Simple Method for Detecting Interactions between a Treatment and a Large Number of Covariates. J Am Stat Assoc. 2014 Oct; 109(508): 1517-1532.

Examples

## Not run: 
data(Sepsis.train)

yvar="survival"
xvars=names(Sepsis.train)[2:12]
trtvar="THERAPY"
trtref="active"
set.seed(123)

filter.res <- filter(data=Sepsis.train,
type="b",
yvar=yvar,
xvars=xvars,
trtvar=trtvar,
trtref=trtref,
pre.filter=20,
filter.method="univariate")

filter.res

set.seed(123)
filter.res <- filter(data=Sepsis.train,
type="b",
yvar=yvar,
xvars=xvars,
trtvar=trtvar,
trtref=trtref,
pre.filter="opt", 
filter.method="glmnet")

filter.res

## End(Not run)

SubgrpID documentation built on May 2, 2019, 8:02 a.m.