Description Usage Arguments Details Value Author(s) See Also

These functions are all methods for class `tmleMSM`

, `summary.tmleMSM`

objects

1 2 3 4 5 6 |

`object` |
an object of class |

`x` |
an object of class |

`...` |
currently ignored. |

`print.tmleMSM`

prints the estimate, standard error, p-value, and 95% confidence interval only. `print.summary.tmleMSM`

, called indirectly by entering the command `summary(result)` (where `result`

has class `tmleMSM`

), outputs additional information.

`estimates` |
matrix of MSM parameter estimates, standard errors, pvalues, upper and lower bounds on 95% confidence intervals |

`sigma` |
variance-covariance matrix |

`Qmodel` |
working model used to obtain initial estimate of |

`Qterms` |
terms in the model for |

`Qcoef` |
coefficient of each term in model for |

`gmodel` |
model used to estimate treatment mechanism |

`gterms` |
terms in the treatment mechanism model |

`gcoef` |
coefficient of each term in model for treatment mechanism |

`gtype` |
description of estimation procedure for treatment mechanism, e.g. "SuperLearner" |

`g.AVmodel` |
model used to estimate h(A,V) (or h(A,T)) |

`g.AVterms` |
terms in the model for h(A,V) |

`g.AVcoef` |
coefficient of each term in model for h(A,V) |

`g.AVtype` |
description of estimation procedure for h(A,V) |

`g.Deltamodel` |
model used to estimate missingness mechanism |

`g.Deltaterms` |
terms in the missingness mechanism model |

`g.Deltacoef` |
coefficient of each term in model for missingness mechanism |

`g.Deltatype` |
description of estimation procedure for missingness |

`psi.Qinit` |
MSM parameter estimates based on initial (untargeted) estimated |

Susan Gruber

tmle documentation built on Oct. 30, 2019, 9:57 a.m.

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