psdesign: Specify a design for a principal surrogate evaluation

Description Usage Arguments


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

pseval documentation built on May 2, 2019, 2:01 a.m.