did (version 1.2.3)

compute.mp.spatt: compute.mp.spatt

Description

compute.mp.spatt does the main work for computing mutliperiod group-time average treatment effects

Usage

compute.mp.spatt(
  flen,
  tlen,
  flist,
  tlist,
  data,
  dta,
  first.treat.name,
  formla,
  xformla,
  tname,
  w,
  panel,
  idname,
  method,
  seedvec,
  se,
  pl,
  cores,
  printdetails
)

Arguments

data

The name of the data.frame that contains the data

first.treat.name

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 should be 0 for observations in the untreated group.

formla

The formula y ~ d where y is the outcome and d is the treatment indicator (d should be binary)

xformla

A optional one sided formula for additional covariates that will be adjusted for. E.g ~ age + education. Additional covariates can also be passed by name using the x paramater.

tname

The name of the column containing the time periods

w

A vector of weights for each observation (not implemented)

panel

Boolean indicating whether the data is panel or repeated cross sections

idname

The individual (cross-sectional unit) id name

method

The method for estimating the propensity score when covariates are included

seedvec

Optional value to set random seed; can possibly be used in conjunction with bootstrapping standard errors#' (not implemented)

se

Boolean whether or not to compute standard errors

pl

Boolean for whether or not to use parallel processing

cores

The number of cores to use for parallel processing

printdetails

Boolean for showing detailed results or not

Value

a list with length equal to the number of groups times the number of time periods; each element of the list contains a QTE object that contains group-time average treamtent effect as well as which group it is for and which time period it is for and the influence function which is used externally to compute standard errors.