trim | R Documentation |
Trims (i.e., truncates) large weights by setting all weights higher than that at a given quantile to the weight at the quantile. This can be useful in controlling extreme weights, which can reduce effective sample size by enlarging the variability of the weights.
## S3 method for class 'wimids'
trim(w, at = 0, lower = FALSE, ...)
w |
A |
at |
Either the quantile of the weights above which weights are to be trimmed (given as a single number between 0.5 and 1) or the number of weights to be trimmed (e.g., |
lower |
Whether also to trim at the lower quantile (e.g., for |
... |
Ignored. |
trim.wimids()
works by calling WeightIt::trim()
on each weightit
object stored in the models
component of the wimids
object. Because trim()
itself is not exported from MatchThem, it must be called using WeightIt::trim()
or by attaching WeightIt (i.e., running library(WeightIt)
) before use.
An object from the wimids
class, identical to the original object except with trim()
applied to each of the weightit
objects in the models
component.
Noah Greifer
WeightIt::trim()
#Loading libraries
library(MatchThem)
#Loading the dataset
data(osteoarthritis)
#Multiply imputing the missing values
imputed.datasets <- mice::mice(osteoarthritis, m = 5)
#Estimating weights of observations in the multiply imputed datasets
weighted.datasets <- weightthem(OSP ~ AGE + SEX + BMI + RAC + SMK,
imputed.datasets,
approach = 'within',
method = 'ps',
estimand = "ATE")
#Trimming the top 10% of weights in each dataset
#to the 90th percentile
trimmed.datasets <- trim(weighted.datasets, at = 0.9)
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