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.
sims
may 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 toFALSE
to turn off bootstrapping. Used for both designs. Must be greater or equal to 100.- merge_by_estimator
A logical. Whether to include
estimator
in 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)