estimate_Q {tmleLite} | R Documentation |
Initial Estimation of Q portion of the Likelihood
Description
An internal function called by the tmle
function to obtain an initial estimate of theQ
portion of the likelihood based on user-supplied values for Q(A,W)
and counterfactual outcomes Q(1,W),Q(0,W)
, or a user-supplied regression formula, or based on a model data-adaptively selected by the DSA
algorithm. If DSA
is not available and Q
is not user-supplied, estimation is based on a main terms regression using glm
.
Usage
estimate_Q(Q, DSAargs, Y, A, W, Delta, family, wts, id)
Arguments
Q |
a 3-column matrix (Q(A,W), Q(1,W), Q(0,W)) , a user-specified regression formula, or NULL . If Q is NULL DSA is used to select a model. If DSA is unavailable estimation is based on a main terms regression using glm |
DSAargs |
an optional list specifying values for all arguments to the DSA algorithm |
Y |
continuous or binary outcome variable |
A |
binary treatment indicator, 1 - treatment, 0 - control |
W |
vector, matrix, or dataframe containing baseline covariates |
Delta |
indicator of missing outcome or treatment assignment. 1 - observed, 0 - missing |
family |
family specification for regressions, generally ‘gaussian’ for continuous oucomes, ‘binomial’ for binary outcomes |
wts |
optional weights on observations. Defaults to unweighted |
id |
id identifying repeated measures |
Value
Q |
a matrix with one row per observation, 3 columns containing the initial estimate of Q(A,W) and predicted values for counterfactual outcomes Q(1,W), Q(0,W) |
coef |
coefficients for each term in working model used for initial estimation of Q |
type |
type of estimation procedure: NULL -user supplied,‘glm’-generalized linear regression using user-specified or main terms model, ‘DSA’-model selected by DSA |
Author(s)
Susan Gruber
See Also
tmle
,
estimate_g
,
DSA
[Package
tmleLite version 1.0-1
Index]