kappaSize (version 1.1)

PowerBinary: Power-Based Approach for the Number of Subjects Required for a Study of Interobserver Agreement with a Binary Outcome

Description

This function provides detailed sample size estimation information to determine the number of subjects that are required to test the hypothesis \(H_0: \kappa = \kappa_0\) vs. \(H_1: \kappa = \kappa_1\), at two-sided significance level \(\alpha\), with power, \(1 - \beta\).

Usage

PowerBinary(kappa0, kappa1, props, raters=2, alpha=0.05, power=0.80)

Arguments

kappa0

The null hypothesis for the \(\kappa\) hypothesis test.

kappa1

The alternate hypothesis for the \(\kappa\) hypothesis test.

props

The anticipated prevalence of the desired trait. Note that specifying props as either a single value, or two values that some to one, provides the same result.

raters

The number of raters that are available. This function allows between 2 and 6 raters.

alpha

The desired type I error rate.

power

The desired level of power, recall power = 1 - type II error.

Value

N

The calculated sample size.

kappa0

The specified null hypothesis.

kappa1

The specified alternative hypothesis.

props

The anticipated proportion of individuals with the outcome.

raters

The number of raters.

alpha

The desired type I error rate.

power

The desired level of power, recall power = 1 - type II error.

Details

This function provides detailed sample size estimation tools for studies of interobserver agreement with a binary outcome. This function employs the power approach, rejecting \(\kappa_0\) in favour of \(\kappa_1\) for a pre-specified significance level and power. Note that a warning message is provided if any of the expected cell counts are less than 5.

References

Donner A, Rotondi MA. (2010). Sample Size Requirements for Interval Estimation of the Kappa Statistic for Interobserver Agreement Studies with a Binary Outcome and Multiple Raters. International Journal of Biostatistics 6:31.

Altaye M, Donner A, Klar N. (2001). Procedures for Assessing Interobserver Agreement among Multiple Raters. Biometrics 57:584-588.

Donner A. (1999). Sample Size Requirements for Interval Estimation of the Intraclass Kappa Statistic. Communication in Statistics 28:415-429.

Bartfay E, Donner A. (2001). Statistical Inferences for Interobserver Agreement Studies with Nominal Outcome Data. The Statistician 50:135-146.

Donner A, Eliasziw M. (1987) Sample size requirements for reliability studies. Statistics in Medicine 6:441-448.

See Also

CIBinary

Examples

# NOT RUN {
Suppose an investigator would like to determine the required sample size to test 
kappa0=0.4 vs. kappa1=0.6 with alpha=0.05 and power=0.80 in a study of 
interobserver agreement.  Further suppose that the prevalence of the trait is 0.30.
# }
# NOT RUN {
PowerBinary(kappa0=0.4, kappa1=0.6, props=0.30, alpha=0.05, power=0.80);
# }