Bootstrap Covariate Data
bootstrap_cov(
external_dat,
n,
imbal_var = NULL,
imbal_prop = NULL,
ref_val = 0
)Data frame of the external data from which to bootstrap covariate vectors
Number of rows in the output dataset
Optional variable indicating which covariate's distribution
should be altered to incorporate imbalance compared to the external data.
If left NULL, the distributions of all covariates in the output dataset
will match the distributions in the external dataset. The imbalance
variable must be binary.
Optional imbalance proportion, required if an imbalance variable is specified. This defines the proportion of individuals with the reference value of the imbalance variable in the returned dataset. This can either be a single proportion or a vector of proportions, in which case a list of datasets is returned.
Optional value corresponding to the reference level of the binary imbalance variable, if specified
Data frame with the same number of columns as the external data frame
and n number of rows (if the length of imbal_prop is 0 or 1); otherwise,
a list of data frames with a length equal to that of imbal_prop
Covariate data can be generated for n individuals enrolled in
the internal trial by bootstrap sampling entire covariate vectors from the
external data, thus preserving the correlation between the covariates. If
both imbal_var = NULL and imbal_prop = NULL, the function returns
a single data frame in which the distributions of each covariate align
with the covariate distributions from the external data (i.e., balanced
covariate distributions across the two trials). Alternatively, covariate
imbalance can be incorporated into the generated sample with respect to a
binary covariate (imbal_var) such that a specified proportion
(imbal_prop) of individuals in the resulting sample will have the
reference level (ref_val) of this imbalance covariate. In this case,
stratified bootstrap sampling is employed with the imbalance covariate as
the stratification factor.
Multiple samples with varying degrees of imbalance can be generated
simultaneously by defining imbal_prop to be a vector of values. The
function then returns a list of data frames with a length equal to the
number of specified imbalance proportions.
# Return one data frame with covariate distributions similar to external data
samp_balance <- bootstrap_cov(ex_binary_df, n = 1000)
# Return a list of two data frames that incorporate imbalance w.r.t. covariate 2
samp_imbalance <- bootstrap_cov(ex_binary_df, n = 1000, imbal_var = cov2,
imbal_prop = c(0.25, 0.5), ref_val = 0)