Generate mappings that describe how variables in the data are mapped to
components of the principal surrogate analysis. Other than data, this
is a list of key-value pairs describing the common elements of a ps analysis.
The required keys are Z, Y, and S. Optional keys are BIP, CPV, BSM, and
weights. These elements are described in details below. Additional keys-value
pairs can be included in .... This function generates an augmented
dataset and additional information for subsequent steps in the analysis. In
the subsequent steps, refer to the variables by the keys. See
add_integration and add_riskmodel for information on how to
proceed in the analysis.
psdesign(data, Z, Y, S, BIP = NULL, CPV = NULL, BSM = NULL,
weights = NULL, tau, ...)Data frame containing data to be analyzed
Expression defining the treatment variable which has 2 levels
Expression defining the outcome variable. For binary events this should be coded as 0/1 or a factor with 2 levels. For censored time-to-event outcomes this can be a call to Surv
Expression defining the candidate surrogate
Optional expression defining the baseline irrelevant predictor
Optional expression defining the closeout placebo vaccination measurement
Optional expression defining the baseline surrogate measurement
optional expression defining weights to accommodate nonrandom subsampling, such as case control or two phase
numeric, When the outcome Y is a survival time, it is possible that the surrogate was measured at some time tau after enrollment. Use the argument tau to specify the time when the surrogate was measured, in study time. Not required for binary Y.
Other key-value pairs that will be included in the augmented data, e.g. additional candidate surrogates, covariates for adjustment, variables used for integration