bate (version 0.1.0)

ovbias_par: Compute bias adjusted treatment effect taking data frame as input.

Description

Compute bias adjusted treatment effect taking data frame as input.

Usage

ovbias_par(
  data,
  outcome,
  treatment,
  control,
  other_regressors = NULL,
  deltalow,
  deltahigh,
  Rhigh,
  e
)

Arguments

data

Data frame.

outcome

Outcome variable.

treatment

Treatment variable.

control

Control variables to add in the intermediate regression.

other_regressors

Subset of control variables to add in the short regression (default is NULL).

deltalow

The lower limit of delta.

deltahigh

The upper limit of delta.

Rhigh

The upper limit of Rmax.

e

The step size.

Value

List with three elements:

Data

Data frame containing the bias and bias-adjusted treatment effect for each point on the grid

bias_Distribution

Quantiles (2.5,5.0,50,95,97.5) of the empirical distribution of bias

bstar_Distribution

Quantiles (2.5,5.0,50,95,97.5) of the empirical distribution of the bias-adjusted treatment effect

Examples

# NOT RUN {
## Load data set
data("NLSY_IQ")
 
## Set parameters for bounded box
Rhigh <- 0.61
deltalow <- 0.01
deltahigh <- 0.99
e <- 0.01

# }
# NOT RUN {
## Compute bias and bias-adjusted treatment effect
OVB_par <- ovbias_par(data=NLSY_IQ,
outcome="iq_std",treatment="BF_months", 
control=c("age","sex","income","motherAge","motherEDU","mom_married","race"), 
other_regressors = c("sex","age"), deltalow=deltalow, 
deltahigh=deltahigh, Rhigh=Rhigh, e=e)

## Default quantiles of bias
OVB_par$bias_Distribution

# Default quantiles of bias-adjusted treatment effect
OVB_par$bstar_Distribution
# }
# NOT RUN {
# }