standardized_mean_differences {OutcomeWeights} | R Documentation |
Calls C++ implementation to calculate standardized mean differences.
Description
Calculates standardized mean differences between treated and controls and towards target means for an outcome weights matrix with potentially many rows like for CATEs.
Usage
standardized_mean_differences(X, treat, omega, target = NULL)
Arguments
X |
Covariate matrix with N rows and p columns. |
treat |
Binary treatment variable. |
omega |
Outcome weights matrix with dimension number of weight vectors for which balancing should be checked x number of training units. |
target |
Optional matrix with dimension number of weight vectors for which balancing should be checked x p indicating the target values the covariates should be balanced towards. If NULL, average of X used as target of ATE. |
Value
3D-array of dimension p x 6 x number of weight vectors for which balancing should be checked where the second dimension provides the following quantities:
"Mean 0": The weighted control mean
"Mean 1": The weighted treated mean
"SMD balancing": Standardized mean differences for covariate balancing (Mean 1 - Mean 0) / sd(X)
"SMD targeting 0": Standardized mean difference to assess targeting of control (Mean 0 - target) / sd(X)
"SMD targeting 1": Standardized mean difference to assess targeting of treated (Mean 1 - target) / sd(X)
References
Rosenbaum, P. R., & Rubin, D. B. (1984). Reducing bias in observational studies using subclassification on the propensity score. Journal of the American Statistical Association, 79 (387), 516–524.