compute_counter_weight function

Compute counter or weight of data samples

Computes counter (for matching approach) or weight (for weighting) approach.

compute_counter_weight(gps_obj, ci_appr, nthread = 1, ...)

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.

Returns

Returns a counter_weight (cgps_cw) object that includes .data and params

attributes.

• .data: includes id and counter_weight columns. In case of matching

  the counter_weight column is integer values, which represent how many times the provided observational data was mached during the matching process. In case of weighting 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 is seq(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

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)