CalAPCEipwRE {aihuman} | R Documentation |
Estimate propensity score and use Hajek estimator to compute APCE. See S7 for more details.
CalAPCEipwRE(data, formula, nAGQ = 1)
data |
A |
formula |
A formula 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. |
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. |
data(synth)
data(hearingdate_synth)
synth$CourtEvent_HearingDate = hearingdate_synth
freq_apce_re = CalAPCEipwRE(synth, formula = "Y ~ Sex + White + Age +
CurrentViolentOffense + PendingChargeAtTimeOfOffense +
PriorMisdemeanorConviction + PriorFelonyConviction +
PriorViolentConviction + (1|CourtEvent_HearingDate) + D")