Calculate covariate effect size differences before and after stratification.
Source:R/covariateBalance.R
covariateBalance.RdThis function is modified from the [PSAgraphics::cv.bal.psa()] function in the `PSAgrpahics` package.
Usage
covariateBalance(
covariates,
treatment,
propensity,
strata = NULL,
int = NULL,
tree = FALSE,
minsize = 2,
universal.psd = TRUE,
trM = 0,
absolute.es = TRUE,
trt.value = NULL,
use.trt.var = FALSE,
verbose = FALSE,
xlim = NULL,
plot.strata = TRUE,
...
)Arguments
- covariates
dataframe of interest
- treatment
binary vector of 0s and 1s (necessarily? what if character, or 1, 2?)
- propensity
PS scores from some method or other.
- strata
either a vector of strata number for each row of covariate, or one number n in which case it is attempted to group rows by ps scores into n strata of size approximately 1/n. This does not seem to work well in the case of few specific propensity values, as from a tree.
- int
either a number m used to divide [0,1] into m equal length subintervals, or a vector of cut points between 0 an 1 defining the subintervals (perhaps as suggested by loess.psa). In either case these subintervals define strata, so strata can be of any size.
- tree
logical, if unique ps scores are few, as from a recursively partitioned tree, then TRUE will force each ps value to define a stratum.
- minsize
smallest allowable stratum-treatment size. If violated, strata is removed.
- universal.psd
If 'TRUE', forces standard deviations used to be unadjusted for stratification.
- trM
trimming proportion for mean calculations.
- absolute.es
logical, if 'TRUE' routine uses absolute values of all effect sizes.
- trt.value
allows user to specify which value is active treatment, if desired.
- use.trt.var
logical, if true then Rubin-Stuart method using only treatment variance with be used in effect size calculations.
- verbose
logical, controls output that is visibly returned.
- xlim
limits for the x-axis.
- plot.strata
logical indicating whether to print strata.
- ...
currently unused.