R/regression_discontinuity_designer.R
regression_discontinuity_designer.Rd
Builds a design with sample from population of size N
. The average treatment effect local to the cutpoint is equal to tau
. It allows for specification of the order of the polynomial regression (poly_reg_order
), cutoff value on the running variable (cutoff
), and size of bandwidth around the cutoff (bandwidth
). By providing a vector of numbers to control_coefs
and treatment_coefs
, users can also specify polynomial regression coefficients that generate the expected control and treatment potential outcomes given the running variable.
regression_discontinuity_designer( N = 1000, tau = 0.15, outcome_sd = 0.1, cutoff = 0.5, bandwidth = 0.5, control_coefs = c(0.5, 0.5), treatment_coefs = c(-5, 1), poly_reg_order = 4, args_to_fix = NULL )
N | An integer. Size of population to sample from. |
---|---|
tau | A number. Difference in potential outcomes functions at the threshold. |
outcome_sd | A positive number. The standard deviation of the outcome. |
cutoff | A number in (0,1). Threshold on running variable beyond which units are treated. |
bandwidth | A number. The value of the bandwidth on both sides of the threshold from which to include units. |
control_coefs | A vector of numbers. Coefficients for polynomial regression function that generates control potential outcomes. Order of polynomial is equal to length. |
treatment_coefs | A vector of numbers. Coefficients for polynomial regression function that generates treatment potential outcomes. Order of polynomial is equal to length. |
poly_reg_order | Integer greater than or equal to 1. Order of the polynomial regression used to estimate the jump at the cutoff. |
args_to_fix | A character vector. Names of arguments to be args_to_fix in design. |
A regression discontinuity design.
See vignette online.
# Generate a regression discontinuity design using default arguments: regression_discontinuity_design <- regression_discontinuity_designer()