FixedNBinary: Calculation of the Lowest Expected Value, kappaL, for a fixed...

In kappaSize: Sample Size Estimation Functions for Studies of Interobserver Agreement

Description

This function provides the potential lower bound for a 100(1 - α) % confidence interval that can be calculated for a fixed sample size, n, and an anticipated value of κ, kappa0. This version assumes that the outcome of interest is binary.

Usage

FixedNBinary(kappa0, n, props, raters=2, alpha=0.05)

Arguments

kappa0	The preliminary value of κ.
n	The total number of available subjects.
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.

Details

This function calculates the expected lower bound of a one-sided confidence interval for a fixed sample size, n, and an anticipated value of κ, kappa0. This function can illustrate the amount of precision available in the estimation of kappa for a fixed sample size. Note that a warning message is provided if any of the expected cell counts are less than 5.

Value

n	The specified sample size.
kappa0	The specified anticipated value of κ.
kappaL	The calculated expected lower limit.
props	The anticipated proportion of individuals with the outcome.
raters	The number of raters.
alpha	The desired type I error rate.
ChiCrit	The critical value that is required for sample size estimation. It is typically not required and is not displayed in the summary output.

Author(s)

Michael Rotondi, [e-mail]

References

Rotondi MA, Donner A. (2012). A Confidence Interval Approach to Sample Size Estimation for Interobserver Agreement Studies with Multiple Raters and Outcomes. Journal of Clinical Epidemiology, 65:778-784.

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.

Examples

## Not run: Suppose an investigator would like to determine the expected lower bound for 
kappa0=0.7 assuming he has access to 100 subjects and 4 raters.  Further suppose that 
the prevalence of the trait is 0.50.
## End(Not run)
FixedNBinary(kappa0=0.7, n=100, props=0.50, alpha=0.05, raters=4);

kappaSize documentation built on May 1, 2019, 9:21 p.m.