Returns the candidate columns that `nlmixr2(..., est = "vae")` would explore during automated covariate selection, using the same discovery rules as the fit: every non-reserved data column that is constant within each subject is a candidate. A numeric candidate with more than two unique values is continuous and contributes one column per eligible shape; anything else is categorical and contributes an indicator per testable level. Columns sharing a `group` are alternate shapes of one covariate, so at most one of them can enter a given parameter. Time-varying columns cannot be searched and are excluded with a warning.
Arguments
- data
estimation dataset containing at least an `ID` column; column names are matched case-insensitively, as in the VAE fit
- warn
when `TRUE` (default) warn about time-varying columns excluded from the search; when `FALSE` exclude them silently
- shapes, covCenterType, covCenter, catCutoff
as in [vaeControl()]; control which shapes are explored and how covariates are centered
Value
a data frame with one row per candidate search column and columns `covariate` (the column name), `raw` (upper-cased data column it comes from), `shape`, `level` (for categorical indicators), `group` (mutual exclusion group), `block` (columns selected all-or-none, i.e. the two arms of a `"hockey"` relationship), `type` and `center`; zero rows when nothing qualifies
Examples
d <- data.frame(id = rep(1:3, each = 2), time = rep(0:1, 3), dv = rnorm(6),
wt = rep(c(70, 80, 60), each = 2),
sex = rep(c(0, 1, 0), each = 2))
vaeCovariates(d)
#> covariate raw shape level group block type center
#> 1 WT_power WT power <NA> 1 1 continuous 70
#> 2 WT_lin WT lin <NA> 1 2 continuous 70
#> 3 WT_hockeyLow WT hockeyLow <NA> 1 3 continuous 70
#> 4 WT_hockeyHi WT hockeyHi <NA> 1 3 continuous 70
#> 5 SEX SEX cat <NA> 2 4 categorical 0
# restrict the explored shapes
vaeCovariates(d, shapes = "power")
#> covariate raw shape level group block type center
#> 1 WT_power WT power <NA> 1 1 continuous 70
#> 2 SEX SEX cat <NA> 2 2 categorical 0