Skip to contents

An object to carry around parameters in the ptetools package

Source: R/pte_params.R
pte_params.Rd

Object that contain pte parameters

Usage

pte_params(
  yname,
  gname,
  tname,
  idname,
  data,
  glist,
  tlist,
  cband,
  alp,
  boot_type,
  anticipation = NULL,
  base_period = NULL,
  weightsname = NULL,
  control_group = "notyettreated",
  gt_type = "att",
  ret_quantile = 0.5,
  global_fun = FALSE,
  time_period_fun = FALSE,
  group_fun = FALSE,
  biters,
  cl
)

Arguments

yname

Name of outcome in data

gname

Name of group in data

tname

Name of time period in data

idname

Name of id in data

data

balanced panel data

glist

list of groups to create group-time average treatment effects for

tlist

list of time periods to create group-time average treatment effects for

cband

whether or not to report a uniform (instead of pointwise) confidence band (default is TRUE)

alp

significance level; default is 0.05

boot_type

which type of bootstrap to use

anticipation

how many periods before the treatment actually takes place that it can have an effect on outcomes

base_period

The type of base period to use. This only affects the numeric value of results in pre-treatment periods. Results in post-treatment periods are not affected by this choice. The default is "varying", where the base period will "back up" to the immediately preceding period in pre-treatment periods. The other option is "universal" where the base period is fixed in pre-treatment periods to be the period right before the treatment starts. "Universal" is commonly used in difference-in-differences applications, but can be unnatural for other identification strategies.

weightsname

The name of the column that contains sampling weights. The defaul is NULL, in which case no sampling weights are used.

control_group

Which group is used as the comparison group. The default choice is "notyettreated", but different estimation strategies can implement their own choices for the control group

gt_type

which type of group-time effects are computed. The default is "att". Different estimation strategies can implement their own choices for gt_type

ret_quantile

For functions that compute quantile treatment effects, this is a specific quantile at which to report results, e.g., ret_quantile = 0.5 will return that the qte at the median.

global_fun

Logical indicating whether or not untreated potential outcomes can be estimated in one shot, i.e., for all groups and time periods. Main use case would be for one-shot imputation estimators. Not supported yet.

time_period_fun

Logical indicating whether or not untreated potential outcomes can be estimated for all groups in the same time period. Not supported yet.

group_fun

Logical indicating whether or not untreated potential outcomes can be estimated for all time periods for a single group. Not supported yet. These functions aim at reducing or eliminating running the same code multiple times.

biters

number of bootstrap iterations; default is 100

cl

number of clusters to be used when bootstrapping; default is 1