Stepwise Covariate Model-selection (SCM) method
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.
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")
})
} # }