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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