treatment_effect {TSDT} | R Documentation |
treatment_effect
Description
Compute treatment effect as mean( treatment response ) - mean( control response )
Usage
treatment_effect(data, scoring_function_parameters = NULL)
Arguments
data |
data.frame containing response data |
scoring_function_parameters |
named list of scoring function control parameters |
Details
This function will compute the treatment for the response. The treatment effect is computed as the difference in means between the non-control treatment arm and the control treatment arm. The user must provide the treatment variable as well as the control value.
Value
The difference in mean response across treatment arms.
See Also
Examples
N <- 100
df <- data.frame( continuous_response = numeric(N),
trt = integer(N) )
df$continuous_response <- runif( min = 0, max = 20, n = N )
df$trt <- sample( c(0,1), size = N, prob = c(0.4,0.6), replace = TRUE )
# Compute the treatment effect
treatment_effect( df, list( y_var = 'continuous_response', trt_control = 0 ) )
# Function return value should match this value
mean( df$continuous_response[df$trt == 1] ) - mean( df$continuous_response[df$trt == 0] )
[Package TSDT version 1.0.7 Index]