Means of each covariate in the treated and comparison groups, their standardised mean difference, and Welch's test, optionally weighted (after matching or weighting).
Details
The standardised mean difference is \((\bar x_1 - \bar x_0) / s_1\) with \(s_1\) the unweighted standard deviation in the treated group (the convention for the effect on the treated, so that it does not move when weights change the comparison group); \(|SMD| < 0.1\) is the usual threshold for balance. With weights the means are weighted and the test uses the weighted variances and Kish's effective sample sizes.
References
Welch BL (1947). The generalization of ‘Student's’ problem when several different population variances are involved. Biometrika 34(1-2):28-35. doi:10.1093/biomet/34.1-2.28
Examples
d <- data.frame(t = rep(0:1, each = 50),
age = c(stats::rnorm(50, 30), stats::rnorm(50, 33)))
baltab(d, "t", "age")
#> ╭── Covariate balance ──────────────────────────────────────────────────╮
#> │ Covariates 1 │
#> │ Largest |SMD| 2.747 │
#> │ Above 0.1 1 │
#> │ │
#> │ covariate mean_treated mean_comparison smd p_value │
#> │ --------- ------------ --------------- ----- ------- │
#> │ age 32.80 30.09 2.747 < 0.001 │
#> │ │
#> │ A standardised mean difference (SMD) below 0.1 in absolute value is │
#> │ usually read as balanced; 1 of 1 covariates are above it. │
#> ╰───────────────────────────────────────────────────────────────────────╯