nlmixr (version 2.0.7)

covarSearchAuto: Stepwise Covariate Model-selection (SCM) method

Description

Stepwise Covariate Model-selection (SCM) method

Usage

covarSearchAuto(
  fit,
  varsVec,
  covarsVec,
  pVal = list(fwd = 0.05, bck = 0.01),
  covInformation = NULL,
  catCovariates = NULL,
  searchType = c("scm", "forward", "backward"),
  restart = FALSE
)

Arguments

fit

an nlmixr 'fit' object

varsVec

a list of candidate variables to which the covariates could be added

covarsVec

a list of candidate covariates that need to be tested

pVal

a named list with names 'fwd' and 'bck' for specifying the p-values for the forward and backward searches, respectively

covInformation

a list containing additionl information on the variables-covariates pairs that should be passed on to addCovMultiple function

catCovariates

a list of covariates that should be treated as categorical

searchType

one of 'scm', 'forward' and 'backward' to specify the covariate search method; default is 'scm'

restart

a boolean that controls if the search should be restarted; default is FALSE

Value

A list summarizing the covariate selection steps and output; This list has the "summaryTable" for the overall summary of the covariate selection as well as "resFwd" for the forward selection method and "resBck" for the backward selection method.

Examples

# NOT RUN {
# }
# NOT RUN {
one.cmt <- function() {
  ini({
    ## You may label each parameter with a comment
    tka <- 0.45 # Log Ka
    tcl <- log(c(0, 2.7, 100)) # Log Cl
    ## This works with interactive models
    ## You may also label the preceding line with label("label text")
    tv <- 3.45; label("log V")
    ## the label("Label name") works with all models
    eta.ka ~ 0.6
    eta.cl ~ 0.3
    eta.v ~ 0.1
    add.sd <- 0.7
  })
  model({
    ka <- exp(tka + eta.ka)
    cl <- exp(tcl + eta.cl)
    v <- exp(tv + eta.v)
    linCmt() ~ add(add.sd)
  })
}

fit <- nlmixr(one.cmt, theo_sd,"focei")
RxODE::.rxWithWd(tempdir(), {# with temporary directory

covarSearchAuto(fit, varsVec = c("ka", "cl"),
    covarsVec = c("WT", "SEX"), catCovariates = c("SEX"))

})

## Note that this didn't include sex, add it to dataset and restart model

d <- theo_sd
d$SEX <-0
d$SEX[d$ID<=6] <-1

fit <- nlmixr(one.cmt, d, "focei")

# This would restart if for some reason the search crashed:

RxODE::.rxWithWd(tempdir(), {# with temporary directory

covarSearchAuto(fit, varsVec = c("ka", "cl"), covarsVec = c("WT", "SEX"),
                catCovariates = c("SEX"), restart = TRUE)

covarSearchAuto(fit, varsVec = c("ka", "cl"), covarsVec = c("WT", "SEX"),
                catCovariates = c("SEX"), restart = TRUE,
                searchType = "forward")
})

# }
# NOT RUN {
# }