trimmer: trimmer

In did: Treatment Effects with Multiple Periods and Groups

trimmer

Description

A utility function to find observations that appear to violate support conditions. This function is not called anywhere in the code, but it is just useful for debugging some common issues that users run into.

Usage

trimmer(
  g,
  tname,
  idname,
  gname,
  xformla,
  data,
  control_group = "notyettreated",
  threshold = 0.999
)

Arguments

g	is a particular group (below I pass in 2009)
tname	The name of the column containing the time periods
idname	The individual (cross-sectional unit) id name
gname	The name of the variable in data that contains the first period when a particular observation is treated. This should be a positive number for all observations in treated groups. It defines which "group" a unit belongs to. It should be 0 for units in the untreated group.
xformla	A formula for the covariates to include in the model. It should be of the form ~ X1 + X2. Default is NULL which is equivalent to xformla=~1. This is used to create a matrix of covariates which is then passed to the 2x2 DID estimator chosen in est_method. For time-varying covariates: (1) With balanced panel data, in each 2x2 comparison, the covariates are taken to be the value of the covariates in the earlier time period, and all of the underlying computation involve change in Y as a function of those values of covariates. (2) With repeated cross sections data and unbalanced panel data, the covariates are taken from each time period and computations involve Y_post conditional on X_post minus Y_pre conditional on X_pre. A byproduct of this is that, with balanced panel data and in the presence of time-varying covariates, it is possible to get different numerical results according to whether or not allow_unbalanced_panel=TRUE or FALSE.
data	The name of the data.frame that contains the data
control_group	Which units to use the control group. The default is "nevertreated" which sets the control group to be the group of units that never participate in the treatment. This group does not change across groups or time periods. The other option is to set group="notyettreated". In this case, the control group is set to the group of units that have not yet participated in the treatment in that time period. This includes all never treated units, but it includes additional units that eventually participate in the treatment, but have not participated yet.
threshold	the cutoff for which observations are flagged as likely violators of the support condition.

Value

list of ids of observations that likely violate support conditions

did documentation built on Dec. 13, 2025, 9:06 a.m.