n_locshift_bound {skewsamp}

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

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 \delta

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)