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Recalculate eta shrinkage from individual estimates

Source: R/utils.R
recalc_shk.Rd

Unlike get_shk(), which parses the eta shrinkage NONMEM itself reported in the output file, this recalculates shrinkage directly from the individual (empirical Bayes) eta estimates found in the data, using the standard \(100 \times (1 - SD(\eta)/\omega)\) formula, where \(\omega\) is the standard deviation implied by the associated diagonal omega estimate.

Usage

recalc_shk(
  xpdb,
  ...,
  .etastype = 1,
  .problem = NULL,
  .subprob = NULL,
  .method = NULL,
  drop_fixed = TRUE,
  quiet
)

Arguments

xpdb

<xpose_dataxpose::xpose_data> or xp_xtras object

...

<tidyselect> Which eta column(s) to recalculate shrinkage for. Defaults to every eta column for .problem.

.etastype

<numeric(1)> 1 (the default) excludes, for each eta, individuals whose estimate is a "true zero" (exactly 0, as opposed to merely shrunk near it) from the calculation; 0 keeps them. See Details.

.problem

<numeric> Problem number to use. Uses the xpose default if not provided.

.subprob

<numeric> Subproblem number to use. Uses the xpose default if not provided.

.method

<character> Method to use. Uses the xpose default if not provided.

drop_fixed

<logical> Drop fixed etas (which have no meaningful shrinkage to recalculate), as in xpose::drop_fixed_cols.

quiet

<logical> Silence extra debugging output

Value

A tibble with one row per eta, reporting the omega used, the number of individuals excluded (if any), and the recalculated shrinkage (as a percentage, to stay consistent with get_shk()).

Details

An eta is a "true zero" for an individual when NONMEM never had grounds to move it away from its prior mean of 0, eg an individual with no observations contributing to the objective function. That is different from an eta that is merely shrunk close to 0 through legitimate estimation, and including "true zero" individuals in the shrinkage calculation biases it, since they carry no information about the actual empirical distribution of etas. .etastype = 1 (the default) excludes them from the calculation; .etastype = 0 reproduces the traditional, unadjusted calculation.

Examples

recalc_shk(xpdb_x)
#> # A tibble: 3 × 8
#>   problem subprob method eta   omega     n n_excluded shrinkage
#>     <dbl>   <dbl> <chr>  <chr> <dbl> <int>      <int>     <dbl>
#> 1       1       1 foce   ETA1  0.27     74          0      52.9
#> 2       1       1 foce   ETA2  0.195    74          0      68.5
#> 3       1       1 foce   ETA3  1.38     74          0      10.2

# Just a subset of etas...
recalc_shk(xpdb_x, ETA1)
#> # A tibble: 1 × 8
#>   problem subprob method eta   omega     n n_excluded shrinkage
#>     <dbl>   <dbl> <chr>  <chr> <dbl> <int>      <int>     <dbl>
#> 1       1       1 foce   ETA1   0.27    74          0      52.9

# Including "true zero" etas in the calculation
recalc_shk(xpdb_x, .etastype = 0)
#> # A tibble: 3 × 8
#>   problem subprob method eta   omega     n n_excluded shrinkage
#>     <dbl>   <dbl> <chr>  <chr> <dbl> <int>      <int>     <dbl>
#> 1       1       1 foce   ETA1  0.27     74          0      52.9
#> 2       1       1 foce   ETA2  0.195    74          0      68.5
#> 3       1       1 foce   ETA3  1.38     74          0      10.2