tests/testthat/_snaps/ps_trim-categorical.md

In propensity: A Toolkit for Calculating and Working with Propensity Scores

ps_trim preserves all treatment groups

Code
  expr
Condition <propensity_no_data_warning>
  Warning in `ps_trim()`:
  One or more groups removed after trimming; returning original data

ps_trim validates delta < 1/k

Code
  expr
Condition <propensity_range_warning>
  Warning in `ps_trim()`:
  Invalid trimming threshold (delta >= 1/k); returning original data

ps_trim errors for unsupported methods with categorical

Code
  expr
Condition <rlang_error>
  Error in `ps_trim()`:
  ! `method` must be one of "ps" or "optimal", not "adaptive".

Code
  expr
Condition <rlang_error>
  Error in `ps_trim()`:
  ! `method` must be one of "ps" or "optimal", not "pctl".

ps_trim requires exposure for categorical

Code
  expr
Condition <propensity_missing_arg_error>
  Error in `ps_trim()`:
  ! `.exposure` must be provided for categorical propensity score trimming.

is_unit_trimmed works for matrix objects

Code
  expr
Condition <propensity_no_data_warning>
  Warning in `ps_trim()`:
  One or more groups removed after trimming; returning original data

ps_trim warns when no column names provided

Code
  expr
Condition <propensity_matrix_no_names_warning>
  Warning:
  Propensity score matrix has no column names.
  i Assuming columns are in factor level order: "A", "B", and "C"
  i This may lead to incorrect results if columns are misaligned.

ps_trim.ps_trim warns about already trimmed scores

Code
  expr
Condition <propensity_already_modified_warning>
  Warning in `ps_trim()`:
  Propensity scores have already been trimmed. Returning original object.

ps_trim handles edge cases consistently with PSweight

Code
  expr
Condition <propensity_no_data_warning>
  Warning in `ps_trim()`:
  One or more groups removed after trimming; returning original data

ps_refit errors when all observations are trimmed for categorical

Code
  expr
Condition <propensity_no_data_warning>
  Warning in `ps_trim()`:
  One or more groups removed after trimming; returning original data

Code
  expr
Condition <propensity_no_data_warning>
  Warning in `ps_trim()`:
  One or more groups removed after trimming; returning original data

Code
  expr
Condition <propensity_no_data_error>
  Error in `ps_refit()`:
  ! No retained rows to refit on (all were trimmed).

ps_refit handles minimal data for categorical exposures

Code
  expr
Condition <propensity_no_data_warning>
  Warning in `ps_trim()`:
  One or more groups removed after trimming; returning original data

wt_ate warns when using trimmed but not refitted categorical PS

Code
  expr
Condition <propensity_no_refit_warning>
  Warning in `wt_ate()`:
  It appears you trimmed your propensity score but did not refit the model.
  i Use `ps_refit()` for more accurate re-estimation.

propensity documentation built on March 3, 2026, 1:06 a.m.