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Compute the individual-level value terms for a single regime

Source: R/value_terms.R
value_terms.Rd

Computes the \(2K+1\) coarsening-level value terms for each individual under a single treatment regime. These include augmentation terms for levels \(r = 1, \ldots, 2K\) and the IPW term for \(R = \infty\) (i.e., \(R = 2K+1\)). When outcome regression models (qs) are provided, the augmented terms are computed; otherwise only the IPW term is non-zero.

Usage

value_terms(df, regime_ind, pis, qs, nus)

Arguments

df

A data frame containing the trial data, including treatment assignments, covariates, outcomes (y), and a kappa column.

regime_ind

A matrix of regime consistency indicators for a single regime, with columns indicating whether each individual followed the regime at each stage.

pis

A data frame of estimated propensity scores with columns pi1, ..., piK.

qs

A list containing outcome regression fitted values for a single regime (as returned by get_q_fits), or NULL for IPW estimation.

nus

A list as returned by get_nu, containing the estimated stage probabilities.

Value

A numeric matrix with nrow(df) rows and \(2K+1\) columns, where each column corresponds to a coarsening-level term in the value estimator.