Skip to contents

Stepwise Covariate Model-selection (SCM) method

Usage

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

Arguments

fit

an nlmixr2 '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

catvarsVec

character vector of categorical covariates that need to be added

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.

Author

Vipul Mann, Matthew Fidler, Vishal Sarsani

Examples

if (FALSE) { # \dontrun{
one.cmt <- function() {
  ini({
    tka <- 0.45; label("Ka")
    tcl <- log(c(0, 2.7, 100)); label("Cl")
    tv <- 3.45; label("V")
    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 <- nlmixr2(one.cmt, nlmixr2data::theo_sd, est = "saem", control = list(print = 0))
rxode2::.rxWithWd(tempdir(), {# with temporary directory

auto1 <- covarSearchAuto(fit, varsVec = c("ka", "cl"),
    covarsVec = c("WT"))

})

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


d <- nlmixr2data::theo_sd
d$SEX <-0
d$SEX[d$ID<=6] <-1

fit <- nlmixr2(one.cmt, d, est = "saem", control = list(print = 0))

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

rxode2::.rxWithWd(tempdir(), {# with temporary directory

auto2 <- covarSearchAuto(fit, varsVec = c("ka", "cl"), covarsVec = c("WT"),
                catvarsVec= c("SEX"), restart = TRUE)

auto3 <- covarSearchAuto(fit, varsVec = c("ka", "cl"), covarsVec = c("WT"),
                catvarsVec=  c("SEX"), restart = TRUE,
                searchType = "forward")
})
} # }