RCT Estimators - Simple Linear Regression approach

Source: R/rct-analysis.R

RCT_estimators_lm is used as a function for RCT_analysis function to provide a simple (or reduced) estimators for RCT analysis using simple linear regression

RCT_estimators_lm(
  control_pre_test,
  control_post_test,
  treatment_pre_test,
  treatment_post_test,
  SESOI_lower = 0,
  SESOI_upper = 0,
  na.rm = FALSE
)

Arguments

control_pre_test

Numeric vector containing Control Pre-test observations
control_post_test

Numeric vector containing Control Post-test observations
treatment_pre_test

Numeric vector containing Treatment Pre-test observations
treatment_post_test

Numeric vector containing Treatment Post-test observations
SESOI_lower

Lower smallest effect size of interest threshold
SESOI_upper

Upper smallest effect size of interest threshold
na.rm

Should NAs be removed? Default is FALSE

Value

Named numeric vector

Examples

set.seed(1666)

RCT_estimators_lm(
  control_pre_test = rnorm(20, 100, 10),
  control_post_test = rnorm(20, 105, 10),
  treatment_pre_test = rnorm(20, 100, 10),
  treatment_post_test = rnorm(20, 120, 10),
  SESOI_lower = -5,
  SESOI_upper = 5
)
#>                SESOI lower                SESOI upper 
#>                -5.00000000                 5.00000000 
#>                SESOI range          Systematic effect 
#>                10.00000000                17.29339553 
#>              Random effect Systematic effect to SESOI 
#>                 9.68390174                 1.72933955 
#>     SESOI to Random effect                     pLower 
#>                 1.03264162                 0.01337697 
#>                pEquivalent                    pHigher 
#>                 0.09252191                 0.89410111