dot-makeLongDataNestedCV: Worker function to make long form data set needed for CVTMLE...

In benkeser/cvtmleAUC: Cross-validated TML estimates of cross-validated area under the receiver operating characteristic curve

Description

Worker function to make long form data set needed for CVTMLE targeting step when nested cv is used

Usage

.makeLongDataNestedCV(x, prediction_list, folds, gn, update = FALSE,
  epsilon_0 = 0, epsilon_1 = 0, tol = 0.001)

Arguments

x	The outer validation fold
prediction_list	The full prediction list
gn	An estimate of the marginal dist. of Y
update	Boolean of whether this is called for initial construction of the long data set or as part of the targeting loop. If the former, cross-validated empirical "density" estimates are used. If the latter these are derived from the targeted cdf.
epsilon_0	If update = TRUE, a vector of TMLE fluctuation parameter estimates used to add the CDF and PDF of Psi(X) to the data set
epsilon_1	Ditto above

Value

A long form data list of a particular set up. Columns are named id (multiple per obs. in validation sample), u (if Yi = 0, these are the unique values of psi(x) in the inner validation samples for psi fit on inner training samples for obs with Y = 1, if Yi = 1, these are values of psi(x) in the inner validation samples for psi fit on inner training samples for obs. with Y = 0), Yi (this id's value of Y), Fn (cross-validation estimated value of the cdf of psi(X) given Y = Yi in the training sample), dFn (cross-validated estimate of the density of psi(X) given Y = (1-Yi) in the training sample), psi (the value of this observations \hat\Psi(P_n,B_n^0)), gn (estimate of marginal of Y e.g., computed in whole sample), outcome (indicator that psix <= u), logit_Fn (the cdf estimate on the logit scale, needed for offset in targeting model).

benkeser/cvtmleAUC documentation built on May 16, 2019, 2:30 a.m.