Compute counter or weight of data samples
Source:R/compute_counter_weight.R
compute_counter_weight.Rd
Computes counter (for matching approach) or weight (for weighting) approach.
Arguments
- gps_obj
A gps object that is generated with
estimate_gps
function. If it is provided, the number of iteration will forced to 1 (Default: NULL).- ci_appr
The causal inference approach. Possible values are:
"matching": Matching by GPS
"weighting": Weighting by GPS
- nthread
An integer value that represents the number of threads to be used by internal packages.
- ...
Additional arguments passed to different models.
Value
Returns a counter_weight (cgps_cw) object that includes .data
and params
attributes.
.data
: includesid
andcounter_weight
columns. In case ofmatching
thecounter_weight
column is integer values, which represent how many times the provided observational data was mached during the matching process. In case ofweighting
the column is double values.params
: Include related parameters that is used for the process.
Details
Additional parameters
Causal Inference Approach (ci_appr)
if ci_appr = 'matching':
bin_seq: A sequence of w (treatment) to generate pseudo population. If
NULL
is passed the default value will be used, which isseq(min(w)+delta_n/2,max(w), by=delta_n)
.dist_measure: Matching function. Available options:
l1: Manhattan distance matching
delta_n: caliper parameter.
scale: a specified scale parameter to control the relative weight that is attributed to the distance measures of the exposure versus the GPS.
Examples
# \donttest{
m_d <- generate_syn_data(sample_size = 100)
gps_obj <- estimate_gps(.data = m_d,
.formula = w ~ cf1 + cf2 + cf3 + cf4 + cf5 + cf6,
gps_density = "normal",
sl_lib = c("SL.xgboost"))
cw_object <- compute_counter_weight(gps_obj = gps_obj,
ci_appr = "matching",
bin_seq = NULL,
nthread = 1,
delta_n = 0.1,
dist_measure = "l1",
scale = 0.5)
# }