View source: R/tmle_estimate_q.R
tmle_estimate_q | R Documentation |
unless super learner not available, or user specifies initial values or a regression formula arguments:
tmle_estimate_q( Y, Z = rep(0, length(Y)), A, W, Delta, Q = NULL, Qbounds, Qform = NULL, maptoYstar, SL.library, cvQinit = F, family, id = 1:length(Y), V = 10, verbose = F )
Y |
outcome |
Z |
intermediate variable between A and Y (default= 0 when no int. var.) |
A |
treatment indicator (1=treatment, 0=control) |
W |
baseline covariates |
Delta |
missingness indicator |
Q |
optional externally estimated values for Q |
Qbounds |
bounds for predicted values |
Qform |
optional regression formula to use for glm if |
maptoYstar |
if TRUE, using logistic fluctuation for bounded, continuous outcomes |
SL.library |
library of prediction algorithms for Super Learner |
cvQinit |
flag, if TRUE, cross-validate SL. |
family |
regression family |
id |
subject identifier |
V |
number of folds for SuperLearner |
verbose |
Set T for extra output |
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