Diagnose and compare designs.
Usage
compare_diagnoses(
design1,
design2,
sims = 500,
bootstrap_sims = 100,
merge_by_estimator = TRUE,
alpha = 0.05
)Arguments
- design1
A design or a diagnosis.
- design2
A design or a diagnosis.
- sims
The number of simulations, defaulting to 1000.
simsmay also be a vector indicating the number of simulations for each step in a design, as described forsimulate_design. Used for both designs.- bootstrap_sims
Number of bootstrap replicates for the diagnosands to obtain the standard errors of the diagnosands, defaulting to
1000. Set toFALSEto turn off bootstrapping. Used for both designs. Must be greater or equal to 100.- merge_by_estimator
A logical. Whether to include
estimatorin the set of columns used for merging. Defaults toTRUE.- alpha
The significance level, 0.05 by default.
Details
The function compare_diagnoses runs a many-to-many merge matching by inquiry and term (if present). If merge_by_estimator equals TRUE, estimator is also included in the merging condition. Any diagnosand that is not included in both designs will be dropped from the merge.
Examples
design_a <-
declare_model(N = 100,
U = rnorm(N),
Y_Z_0 = U,
Y_Z_1 = U + rnorm(N, mean = 2, sd = 2)) +
declare_inquiry(ATE = mean(Y_Z_1 - Y_Z_0)) +
declare_assignment(Z = complete_ra(N, prob = 0.5)) +
declare_measurement(Y = reveal_outcomes(Y ~ Z)) +
declare_estimator(Y ~ Z, inquiry = "ATE")
design_b <- replace_step(
design_a, step = "assignment",
declare_assignment(Z = complete_ra(N, prob = 0.3)) )
comparison <- compare_diagnoses(design_a, design_b, sims = 40)