Pilot viability band

Compute a necessary viability screen for pilot sizes before choosing a pilot/main-wave split.

Usage

pilot_viability_band(
  n,
  sigma1,
  sigma0,
  alpha = 0.05,
  method = c("bounded", "bernoulli"),
  input = c("sd", "variance"),
  accounting = c("design_only", "pooled"),
  strict_upper = TRUE
)

Arguments

n

Total experimental sample size across pilot and main wave.

sigma1

Treatment-arm standard deviation, or variance when input = "variance".

sigma0

Control-arm standard deviation, or variance when input = "variance".

alpha

Target error level.

method

Planning method, either "bounded" or "bernoulli".

input

Whether sigma1 and sigma0 are standard deviations ("sd") or variances ("variance").

accounting

"design_only" applies the break-even pilot-share cap; "pooled" ignores that cap.

strict_upper

If TRUE, feasible pilot sizes must be strictly below the design-only break-even cap.

Value

A list of class cmr_pilot_viability_band with total sample size, standard deviations, method, break-even share and total, activation threshold, feasible even pilot sizes, and min/max feasible pilot sizes.

See also

Other pilot planning: activation_threshold_bounded(), break_even_pilot_share(), pilot_plan()

Examples

pilot_viability_band(n = 3000, sigma1 = 0.18, sigma0 = 0.28)
#> $n
#> [1] 3000
#> 
#> $sigma
#> $sigma$sigma1
#> [1] 0.18
#> 
#> $sigma$sigma0
#> [1] 0.28
#> 
#> 
#> $alpha
#> [1] 0.05
#> 
#> $method
#> [1] "bounded"
#> 
#> $accounting
#> [1] "design_only"
#> 
#> $break_even_share
#> [1] 0.04512635
#> 
#> $break_even_total
#> [1] 135.3791
#> 
#> $activation_threshold
#> [1] 72
#> 
#> $strict_upper
#> [1] TRUE
#> 
#> $feasible_pilot_sizes
#>  [1]  72  74  76  78  80  82  84  86  88  90  92  94  96  98 100 102 104 106 108
#> [20] 110 112 114 116 118 120 122 124 126 128 130 132 134
#> 
#> $min_feasible
#> [1] 72
#> 
#> $max_feasible
#> [1] 134
#> 
#> $nonempty
#> [1] TRUE
#> 
#> attr(,"class")
#> [1] "cmr_pilot_viability_band" "list"