DynTxRegime: newOWL – R documentation

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newOWL

Complete an OWL Analysis

Complete an OWL Analysis

.newOWL(
  moPropen,
  data,
  response,
  txName,
  lambdas,
  cvFolds,
  kernel,
  fSet,
  surrogate,
  suppress,
  guess,
  ...
)

`moPropen`	modelObj for propensity modeling
`data`	data.frame of covariates
`response`	Vector of responses
`txName`	Tx variable column header in data
`lambdas`	Tuning parameter(s)
`cvFolds`	Number of cross-validation folds
`kernel`	Kernel object or SubsetList
`fSet`	NULL or function defining subset rules
`surrogate`	Surrogate object
`suppress`	T/F indicating if prints to screen are executed
`guess`	optional numeric vector providing starting values for optimization methods
`...`	Additional inputs for optimization
`txVec`	Tx vector recast as +/- 1

An OWL object

Methods for Estimating Optimal Dynamic Treatment Regimes

v4.10

GPL-2

Authors

S. T. Holloway, E. B. Laber, K. A. Linn, B. Zhang, M. Davidian, and A. A. Tsiatis

Initial release

2022-06-05