Caps weights above a limit and, optionally, redistributes the excess among the others to preserve the weighted total (Potter 1988, 1990; Liu et al. 2004). Optional step that can be inserted anywhere in the recipe, even several times. Operates on the CURRENT weights at that point of the cascade.
Usage
step_trim(
spec,
max_ratio,
min_ratio = NULL,
reference = c("base", "median", "value"),
redistribute = TRUE,
by = NULL,
maxit = 50L
)Arguments
- spec
a weighting_spec.
- max_ratio
number. Upper cap. Its meaning depends on
reference. E.g. with reference = "base" and max_ratio = 4, no weight may exceed 4 times its design weight.- min_ratio
number or NULL. Lower floor (same units as max_ratio).
- reference
"base" (multiple of each unit's base weight), "median" (multiple of the median of current weights) or "value" (absolute weight value).
- redistribute
logical. If TRUE, redistributes the trimmed excess among the uncapped weights to preserve the total (iterating). If you calibrate afterwards you can use FALSE: calibration restores the totals.
- by
character. Groups within which to redistribute (optional).
- maxit
integer. Maximum cap+redistribution iterations.
Details
There is no standard threshold: max_ratio is an analyst decision, a
bias-variance trade-off. Use Kish's design effect (see summary) to judge
whether trimming is worth it.
Examples
weighting_spec(sample_survey, base_weights = pw) |>
step_trim(max_ratio = 3, reference = "base")
#>
#> == Weighting specification (weightflow) ==
#> Data : 467 cases
#> Base wts: pw
#> Steps :
#> 1. trimming (base, cap 3)
#> Status : not estimated
#>