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Calls C++ implementation to calculate standardized mean differences.

Source: R/diagnostics.R
standardized_mean_differences.Rd

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.