compute_counter_weight {CausalGPS}

Compute counter or weight of data samples

Description

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

Usage

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.

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.

Value

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.

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)