Diagnose and compare designs.

compare_diagnoses( design1, design2, sims = 500, bootstrap_sims = 100, merge_by_estimator = TRUE, alpha = 0.05 )

design1 | A design or a diagnosis. |
---|---|

design2 | A design or a diagnosis. |

sims | The number of simulations, defaulting to 1000. |

bootstrap_sims | Number of bootstrap replicates for the diagnosands to obtain the standard errors of the diagnosands, defaulting to |

merge_by_estimator | A logical. Whether to include |

alpha | The significance level, 0.05 by default. |

A list with a `data.frame`

of compared diagnoses and both diagnoses.

The function `compare_diagnoses`

runs a many-to-many merge matching by `estimand_label`

and `term`

(if present). If `merge_by_estimator`

equals `TRUE`

, `estimator_label`

is also included in the merging condition. Any diagnosand that is not included in both designs will be dropped from the merge.

design_a <- declare_population(N = 100, u = rnorm(N)) + declare_potential_outcomes( Y_Z_0 = u, Y_Z_1 = u + rnorm(N, mean = 2, sd = 2)) + declare_assignment(prob = 0.5) + declare_estimand(ATE = mean(Y_Z_1 - Y_Z_0)) + reveal_outcomes() + declare_estimator(Y ~ Z, estimand = "ATE") design_b <- replace_step(design_a, step = "assignment", declare_assignment(prob = 0.3) ) comparison <- compare_diagnoses(design_a, design_b, sims = 40)