Description Usage Arguments Details Value

View source: R/simulate-su-hill.R

Sample *n* observations with the following scheme:

Covariates:

*X_j ~ N(0,1)*.Assignment:

*Z ~ Bin(n, p)*with*p = logit^{-1}(a + X γ^L + Q γ^N)*where*a = ω - mean(X γ^L + Q γ^N)*.Mean response:

*E(Y(0)|X) = X β_0^L + Q β_0^N*and*E(Y(1)|X) = X β_1^L + Q β_1^N*.Observation:

*Y ~ N(μ,σ_y^2))*.

Superscript *L* denotes the linear components, whilst *N* denotes the non-linear
components.

1 2 3 4 5 6 7 8 9 10 11 12 |

`n` |
Size of simulated sample. |

`treatment_linear` |
Treatment assignment mechanism is linear? |

`response_parallel` |
Response surface is parallel? |

`response_aligned` |
Response surface is aligned? |

`y_sd` |
Observation noise. |

`tau` |
Treatment effect for parallel response surfaces. Not applicable if surface is nonparallel. |

`omega` |
Offset to control treatment assignment ratios. |

`add_categorical` |
Should a categorical variable be added? (Not in Hill and Su) |

`coef_categorical_treatment` |
What are the coefficients of the categorical variable under treatment? (Not in Hill and Su) |

`coef_categorical_nontreatment` |
What are the coefficients of the categorical variable under nontreatment? (Not in Hill and Su) |

Coefficients used are returned in the list this function creates. See Table 1 in Su and Hill (2013) for the table of coefficients.
The *X_j* are in a data.frame named `data`

in the returned list.
The formula for the model matrix *[X,Q]* is named `su_hill_formula`

in the returned list.
The coefficients used for the model matrix are contained in `coefs`

.
The Su and Hill (2013) simulations did not include categorical variables, but you can add them here using arguments: `add_categorical`

, `coef_categorical_treatment`

, `coef_categorical_nontreatment`

.

Hill, Jennifer; Su, Yu-Sung. Ann. Appl. Stat. 7 (2013), no. 3, 1386–1420. doi:10.1214/13-AOAS630. https://projecteuclid.org/euclid.aoas/1380804800

An object of class `suhillsim`

that is a list with elements

`data` |
Simulated data in data.frame |

`mean_y` |
The mean y values for each individual (row) |

`args` |
List of arguments passed to function |

`formulas` |
Response formulas used to generate data |

`coefs` |
Coefficients for the formulas |

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