n_locshift_bound: Compute an upper bound the sample size based on two pilot...

In skewsamp: Estimate Sample Sizes for Group Comparisons with Skewed Distributions

Description

Based on the procedure described by Chakraborti, Hong, & van de Wiel (2006)

Usage

n_locshift_bound(
  s1,
  s2,
  delta,
  alpha = 0.05,
  power = 0.9,
  quantile = 0.9,
  n_resamples = 500,
  q = 0.5
)

Arguments

s1, s2	Pilot samples
delta	numeric value, location shift parameter δ
alpha	Type I error probability
power	1 - Type II error probability, the desired statistical power
quantile	Quantile to use as the upper bound.
n_resamples	number of resamples to use in bootstrapping
q	size of group0 relative to total sample size.

Details

WARNING: Note that the underlying estimation has high variability due to its dependence on pilot samples. The smaller the pilot sample, the more uncertain is the estimation of the required sample size. In a simulation study, we found that the underlying method may also be inaccurate on average, depending on the investigated data.

Value

Returns an object of class "sample_size". It contains the following components:

n	the total sample size
n0	sample size in Group 0 (control group)
n1	sample size in Group 1 (treatment group)
two_sided	logical, TRUE, if the estimated sample size refers to a two-sided test
alpha	type I error rate used in sample size estimation
power	target power used in sample size estimation
effect	effect size used in sample size estimation
effect_type	short description of the type of effect size
comment	additional comment, if there is any
call	the matched call.

References

Chakraborti, S., Hong, B., & van de Wiel, M. A. (2006). A note on sample size determination for a nonparametric test of location. Technometrics, 48(1), 88–94. https://doi.org/10.1198/004017005000000193

Examples

## Not run: 
n_locshift_bound(s1 = rexp(10), s2 = rexp(10),
           delta = 0.35, alpha = 0.05, power = 0.9, n_resamples = 5)
## End(Not run)

skewsamp documentation built on Dec. 17, 2021, 1:07 a.m.