BootstrapAPCEipwRE {aihuman} | R Documentation |
Bootstrap for estimating variance of APCE with random effects
Description
Estimate variance of APCE for frequentist analysis with random effects using bootstrap. See S7 for more details.
Usage
BootstrapAPCEipwRE(
data,
rep = 1000,
fixed,
random,
CourtEvent_HearingDate,
nAGQ = 1
)
Arguments
data |
A |
rep |
Size of bootstrap |
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. |
CourtEvent_HearingDate |
The court event hearing date. |
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.boot |
An array with dimension rep by (k+1) by (k+2) for quantity P(D(1)=d| R=r), dimension 1 is rep (size of bootstrap), dimension 2 is (k+1) values of D from 0 to k, dimension 3 is (k+2) values of R from 0 to k+1. |
P.D0.boot |
An array with dimension rep by (k+1) by (k+2) for quantity P(D(0)=d| R=r). |
APCE.boot |
An array with dimension rep by (k+1) by (k+2) for quantity P(D(1)=d| R=r)-P(D(0)=d| R=r). |
P.R.boot |
An array with dimension rep by (k+2) for quantity P(R=r) for r from 0 to (k+1). |
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
set.seed(123)
boot_apce_re <- BootstrapAPCEipwRE(synth,
fixed = "Y ~ Sex + White + Age +
CurrentViolentOffense + PendingChargeAtTimeOfOffense +
PriorMisdemeanorConviction + PriorFelonyConviction +
PriorViolentConviction + D",
random = "~ 1|CourtEvent_HearingDate"
)