est_samp {txshift}

Estimate Probability of Censoring by Two-Phase Sampling

Description

Estimate Probability of Censoring by Two-Phase Sampling

Usage

est_samp(V, C_samp, fit_type = c("sl", "glm"), sl_learners = NULL)

Arguments

V

A numeric vector, matrix, data.frame or similar object giving the observed values of the covariates known to potentially inform the sampling mechanism.

C_samp

A numeric vector of observed values of the indicator for inclusion in the second-phase sample.

fit_type

A character indicating whether to perform the fit using GLMs or a Super Learner ensemble model. If use of Super Learner is desired, then the argument sl_learners must be provided.

sl_learners

An sl3 Lrnr_sl object, a Super Learner ensemble or learner instantiated externally using sl3.

Details

Compute estimates of the sampling probability for inclusion in the the second-phase via the two-phase sampling mechanism. These estimates are used for the creation of inverse probability weights.

Value

A numeric vector of the estimated sampling mechanism.