ssize.auc.ci: Sample Size Calculations for AUC

In stamats/MKpower: Power Analysis and Sample Size Calculation

Sample Size Calculations for AUC

Description

Compute sample size, power, delta, or significance level of a diagnostic test for an expected AUC.

Usage

ssize.auc.ci(AUC = NULL, delta = NULL, n = NULL, sig.level = 0.05,
             power = NULL, prev = NULL, NMAX = 1e4)

Arguments

AUC	Expected AUC.
n	Total sample size (number of cases + number of controls).
delta	AUC-delta is used as lower confidence limit
sig.level	Significance level (Type I error probability)
power	Assurance probability of confidence interval (1 minus Type II error probability)
prev	Expected prevalence, if NULL prevalence is ignored which means prev = 0.5 is assumed.
NMAX	Maximum sample size considered.

Details

Exactly one of the parameters n, delta, sig.level, and power must be passed as NULL, and that parameter is determined from the others. Notice that sig.level has a non-NULL default so NULL must be explicitly passed if you want to compute it.

The computations use the variance of the AUC derived by Hanley and McNeil (1982) and incorporate an additional assurance probability (power) as in the approach of Flahault et al. (2005).

As noted in Chu and Cole (2007) power is not a monotonically increasing function in n but rather saw toothed (see also Chernick and Liu (2002)). Hence, in our calculations we use the more conservative approach II); i.e., the minimum sample size n such that the actual power is larger or equal power andsuch that for any sample size larger than n it also holds that the actual power is larger or equal power.

Value

Object of class "power.htest", a list of the arguments (including the computed one) augmented with method and note elements.

Note

uniroot is used to solve the equations for unknowns, so you may see errors from it, notably about inability to bracket the root when invalid arguments are given.

Author(s)

Matthias Kohl [e-mail]

References

A. Flahault, M. Cadilhac, and G. Thomas (2005). Sample size calculation should be performed for design accuracy in diagnostic test studies. Journal of Clinical Epidemiology, 58(8):859-862.

J.A. Hanley, B.J. McNeil (1982). The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology, 143(1):29-36.

See Also

uniroot

Examples

## compute n
ssize.auc.ci(AUC = 0.9, delta = 0.05, power = 0.8)
## compute delta
ssize.auc.ci(AUC = 0.9, n = 254, power = 0.8)
## compute power
ssize.auc.ci(AUC = 0.9, n = 254, delta = 0.05)
## compute sig.level
ssize.auc.ci(AUC = 0.9, n = 254, delta = 0.05, power = 0.8, sig.level = NULL)

stamats/MKpower documentation built on Sept. 26, 2024, 7:25 p.m.