Description Usage Arguments Value References Examples

`att`

is used to estimate the difference in mean outcome among treated subjects had a binary (unconfounded) treatment been withheld.

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`y` |
outcome of interest. |

`a` |
binary treatment. |

`x` |
covariate matrix. |

`nsplits` |
integer number of sample splits for nuisance estimation. If nsplits=1, sample splitting is not used, and nuisance functions are estimated on full sample (in which case validity of SEs/CIs requires empirical process conditions). Otherwise must have nsplits>1. |

`sl.lib` |
algorithm library if using SuperLearner. Default library includes "earth", "gam", "glm", "glmnet", "glm.interaction", "mean", and "ranger". |

A list containing the following components:

`res` |
estimates/SEs/CIs/p-values for treated means and contrast. |

`nuis` |
subject-specific estimates of nuisance functions (i.e., propensity score and outcome regression) |

`ifvals` |
vector of estimated influence function values. |

(Also see references for function `ate`

)

Kennedy EH, Sjolander A, Small DS (2015). Semiparametric causal inference in matched cohort studies. *Biometrika*.

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