Tidy diagnosis
Usage
# S3 method for class 'diagnosis'
tidy(x, conf.int = TRUE, conf.level = 0.95, ...)Arguments
- x
A diagnosis object generated by
diagnose_design.- conf.int
Logical indicating whether or not to include a confidence interval in the tidied output. Defaults to ‘TRUE’.
- conf.level
The confidence level to use for the confidence interval if ‘conf.int = TRUE’. Must be strictly greater than 0 and less than 1. Defaults to 0.95, which corresponds to a 95 percent confidence interval.
- ...
extra arguments (not used)
Value
A data.frame with columns for diagnosand names, estimated diagnosand values, bootstrapped standard errors and confidence intervals
Examples
effect_size <- 0.1
design <-
declare_model(
N = 100,
U = rnorm(N),
X = rnorm(N),
potential_outcomes(Y ~ effect_size * Z + X + U)
) +
declare_inquiry(ATE = mean(Y_Z_1 - Y_Z_0)) +
declare_assignment(Z = complete_ra(N)) +
declare_measurement(Y = reveal_outcomes(Y ~ Z)) +
declare_estimator(Y ~ Z, inquiry = "ATE", label = "unadjusted") +
declare_estimator(Y ~ Z + X, inquiry = "ATE", label = "adjusted")
diagnosis <- diagnose_design(design, sims = 100)
tidy(diagnosis)
#> design inquiry estimator outcome term diagnosand estimate std.error
#> 1 design ATE adjusted Y Z mean_estimand 0.100000000 0.00000000
#> 2 design ATE adjusted Y Z mean_estimate 0.106847268 0.02032314
#> 3 design ATE adjusted Y Z bias 0.006847268 0.02032314
#> 4 design ATE adjusted Y Z sd_estimate 0.192082695 0.01165459
#> 5 design ATE adjusted Y Z rmse 0.191242488 0.01166300
#> 6 design ATE adjusted Y Z power 0.080000000 0.02402356
#> 7 design ATE adjusted Y Z coverage 0.980000000 0.01383014
#> 8 design ATE unadjusted Y Z mean_estimand 0.100000000 0.00000000
#> 9 design ATE unadjusted Y Z mean_estimate 0.123325022 0.02402709
#> 10 design ATE unadjusted Y Z bias 0.023325022 0.02402709
#> 11 design ATE unadjusted Y Z sd_estimate 0.246169931 0.01727510
#> 12 design ATE unadjusted Y Z rmse 0.246044092 0.01748903
#> 13 design ATE unadjusted Y Z power 0.040000000 0.01695955
#> 14 design ATE unadjusted Y Z coverage 0.960000000 0.01735081
#> conf.low conf.high
#> 1 0.10000000 0.10000000
#> 2 0.06332808 0.13999793
#> 3 -0.03667192 0.03999793
#> 4 0.17005939 0.21190144
#> 5 0.17022372 0.21499107
#> 6 0.04000000 0.13000000
#> 7 0.95000000 1.00000000
#> 8 0.10000000 0.10000000
#> 9 0.07724880 0.16584713
#> 10 -0.02275120 0.06584713
#> 11 0.20996366 0.27563946
#> 12 0.20948968 0.27517201
#> 13 0.01000000 0.07000000
#> 14 0.93000000 0.99000000