CalAPCEipwRE: Compute APCE using frequentist analysis with random effects

In aihuman: Experimental Evaluation of Algorithm-Assisted Human Decision-Making

Compute APCE using frequentist analysis with random effects

Description

Estimate propensity score and use Hajek estimator to compute APCE. See S7 for more details.

Usage

CalAPCEipwRE(data, fixed, random, nAGQ = 1)

Arguments

data	A data.frame or matrix of which columns consists of pre-treatment covariates, a binary treatment (Z), an ordinal decision (D), and an outcome variable (Y). The column names of the latter three should be specified as "Z", "D", and "Y" respectively.
fixed	A formula for the fixed-effects part of the model to fit.
random	A formula for the random-effects part of the model to fit.
nAGQ	Integer scalar - the number of points per axis for evaluating the adaptive Gauss-Hermite approximation to the log-likelihood. Defaults to 1, corresponding to the Laplace approximation.

Value

An object of class list with the following elements:

P.D1	An array with dimension (k+1) by (k+2) for quantity P(D(1)=d| R=r), dimension 1 is (k+1) values of D from 0 to k, dimension 2 is (k+2) values of R from 0 to k+1.
P.D0	An array with dimension (k+1) by (k+2) for quantity P(D(0)=d| R=r).
APCE	An array with dimension (k+1) by (k+2) for quantity P(D(1)=d| R=r)-P(D(0)=d| R=r).
P.R	An array with dimension (k+2) for quantity P(R=r) for r from 0 to (k+1).
alpha	An array with estimated alpha.
delta	An array with estimated delta.

References

Imai, K., Jiang, Z., Greiner, D.J., Halen, R., and Shin, S. (2023). "Experimental evaluation of algorithm-assisted human decision-making: application to pretrial public safety assessment." Journal of the Royal Statistical Society: Series A. <DOI:10.1093/jrsssa/qnad010>.

Examples

data(synth)
data(hearingdate_synth)
synth$CourtEvent_HearingDate <- hearingdate_synth
freq_apce_re <- CalAPCEipwRE(synth,
  fixed = "Y ~ Sex + White + Age +
                   CurrentViolentOffense + PendingChargeAtTimeOfOffense +
                   PriorMisdemeanorConviction + PriorFelonyConviction +
                   PriorViolentConviction + D",
  random = "~ 1|CourtEvent_HearingDate"
)

aihuman documentation built on April 12, 2025, 1:47 a.m.