ovbias {bate} R Documentation

## Compute bias adjusted treatment effect taking parameter vector as input.

### Description

Compute bias adjusted treatment effect taking parameter vector as input.

### Usage

ovbias(parameters, deltalow, deltahigh, Rhigh, e)


### Arguments

 parameters A vector of parameters (real numbers) that is generated by estimating the short, intermediate and auxiliary regressions. 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 ($bias) and bias-adjusted treatment effect ($bstar) 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

## Load data set
data("NLSY_IQ")

## Set age and race as factor variables
NLSY_IQ$age <- factor(NLSY_IQ$age)
NLSY_IQ$race <- factor(NLSY_IQ$race)

## Collect parameters from the short, intermediate and auxiliary regressions
parameters <- collect_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"))

## Set limits for the bounded box
Rlow <- parameters$Rtilde Rhigh <- 0.61 deltalow <- 0.01 deltahigh <- 0.99 e <- 0.01 ## Not run: ## Compute bias and bias-adjusted treatment effect OVB <- ovbias( parameters = parameters, deltalow=deltalow, deltahigh=deltahigh, Rhigh=Rhigh, e=e) ## Default quantiles of bias (OVB$bias_Distribution)

## Chosen quantilesof bias
quantile(OVB$Data$bias, c(0.01,0.05,0.1,0.9,0.95,0.975))

## Default quantiles of bias-adjusted treatment effect
(OVB$bstar_Distribution) ## Chosen quantiles of bias-adjusted treatment effect quantile(OVB$Data\$bstar, c(0.01,0.05,0.1,0.9,0.95,0.975))

## End(Not run)



[Package bate version 0.1.0 Index]