Confidence Interval Approach for the Number of Subjects Required for a Study of Interobserver Agreement with Three Outcome Categories

Description

This function provides detailed sample size estimation information to determine the number of subjects required using the confidence interval perspective to sample size estimation for \kappa. This version assumes that the outcome has three categories.

Usage

CI3Cats(kappa0, kappaL, kappaU=NA, props, raters=2, alpha=0.05)

Arguments

Details

This function provides detailed sample size estimation computation for studies of interobserver agreement with three outcomes. This function employs the confidence interval perspective, determining the correct sample size that provides the specified expected confidence limits. Sample size estimation is based on the precision of the estimate, instead of a simple hypothesis testing perspective. Note that a warning message is provided if any of the expected cell counts are less than 5.

Value

Author(s)

Michael Rotondi, mrotondi@yorku.ca

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.

See Also

Power3Cats

Examples

## Not run: Suppose an investigator would like to determine the required sample size to test 
kappa0=0.4 with precision of 0.2 on each side, in a study of interobserver agreement 
(3 raters).  Further suppose that the prevalence of the traits are 0.30, 0.2, 0.5.
## End(Not run)

CI3Cats(kappa0=0.4, kappaL=0.3, kappaU=0.6, props=c(0.30, 0.2, 0.5), raters=3, alpha=0.05);

Confidence Interval Approach for the Number of Subjects Required for a Study of Interobserver Agreement with Four Outcome Categories

Description

This function provides detailed sample size estimation information to determine the number of subjects required using the confidence interval perspective to sample size estimation for \kappa. This version assumes that the outcome has four categories.

Usage

CI4Cats(kappa0, kappaL, kappaU=NA, props, raters=2, alpha=0.05)

Arguments

Details

This function provides detailed sample size estimation computation for studies of interobserver agreement with four outcomes. This function employs the confidence interval perspective, determining the correct sample size that provides the specified expected confidence limits. Sample size estimation is based on the precision of the estimate, instead of a simple hypothesis testing perspective. Note that a warning message is provided if any of the expected cell counts are less than 5.

Value

Author(s)

Michael Rotondi, mrotondi@yorku.ca

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.

See Also

Power4Cats

Examples

## Not run: Suppose an investigator would like to determine the required sample size to test 
kappa0=0.4 with precision of 0.1 on each side, in a study of interobserver agreement. 
Further suppose that the prevalence of the traits are 0.30, 0.2, 0.2, 0.3.
## End(Not run)

CI4Cats(kappa0=0.4, kappaL=0.3, kappaU=0.5, props=c(0.30, 0.2, 0.2, 0.3), alpha=0.05);

Confidence Interval Approach for the Number of Subjects Required for a Study of Interobserver Agreement with Five Outcome Categories

Description

This function provides detailed sample size estimation information to determine the number of subjects required using the confidence interval perspective to sample size estimation for \kappa. This version assumes that the outcome has five categories.

Usage

CI5Cats(kappa0, kappaL, kappaU=NA, props, raters=2, alpha=0.05)

Arguments

Details

This function provides detailed sample size estimation computation for studies of interobserver agreement with five outcomes. This function employs the confidence interval perspective, determining the correct sample size that provides the specified expected confidence limits. Sample size estimation is based on the precision of the estimate, instead of a simple hypothesis testing perspective. Note that a warning message is provided if any of the expected cell counts are less than 5.

Value

Author(s)

Michael Rotondi, mrotondi@yorku.ca

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.

See Also

Power5Cats

Examples

## Not run: Suppose an investigator would like to determine the required sample size to test 
kappa0=0.4 with precision of 0.1 on each side, in a study of interobserver agreement.  
Further suppose that the prevalence of the traits are 0.13, 0.17, 0.2, 0.2, 0.3.
## End(Not run)

CI5Cats(kappa0=0.4, kappaL=0.3, kappaU=0.5, props=c(0.13, 0.17, 0.2, 0.2, 0.3), alpha=0.05);

Confidence Interval 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 required using the confidence interval perspective to sample size estimation for \kappa. This version assumes that the outcome has two categories.

Usage

CIBinary(kappa0, kappaL, kappaU=NA, props, raters=2, alpha=0.05)

Arguments

Details

This function provides detailed sample size estimation computation for studies of interobserver agreement with a binary outcome. This function employs the confidence interval perspective, determining the correct sample size that provides the specified expected confidence limits. Sample size estimation is based on the precision of the estimate, instead of a simple hypothesis testing perspective. Note that a warning message is provided if any of the expected cell counts are less than 5.

Value

Author(s)

Michael Rotondi, mrotondi@yorku.ca

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.

See Also

PowerBinary

Examples

## Not run: Suppose an investigator would like to determine the required sample size to test
kappa0=0.4 with precision of 0.1 on each side, in a study of interobserver agreement. 
Further suppose that the prevalence of the trait of interest is 0.30.
## End(Not run)
CIBinary(kappa0=0.4, kappaL=0.3, kappaU=0.5, props=0.30, alpha=0.05);

Calculation of the Lowest Expected Value, kappaL for a fixed sample size in a Study of Interobserver Agreement with a Multinomial Outcome (3 Levels)

Description

This function provides the potential lower bound for a 100(1 - \alpha) % confidence interval that can be calculated for a fixed sample size, n, and an anticipated value of \kappa. This version assumes that the outcome has three categories.

Usage

FixedN3Cats(kappa0, n, props, raters=2, alpha=0.05)

Arguments

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 \kappa, 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

Author(s)

Michael Rotondi, mrotondi@yorku.ca

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 80 subjects and 5 raters.  Further suppose that 
the prevalence of the trait is 0.50.
## End(Not run)
FixedN3Cats(kappa0=0.7, n=80, props=c(0.33, 0.34, 0.33), alpha=0.05, raters=5);

Calculation of the Lowest Expected Value, kappaL, for a fixed sample size in a Study of Interobserver Agreement with a Multinomial Outcome (4 Levels)

Description

This function provides the potential lower bound for a 100(1 - \alpha) % confidence interval that can be calculated for a fixed sample size, n, and an anticipated value of \kappa, kappa0. This version assumes that the outcome of interest has four levels.

Usage

FixedN4Cats(kappa0, n, props, raters=2, alpha=0.05)

Arguments

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 \kappa, 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

Author(s)

Michael Rotondi, mrotondi@yorku.ca

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 80 subjects and 5 raters.  Further suppose that 
the prevalence of the traits of interest are 0.4, 0.4, 0.1, 0.1.
## End(Not run)
FixedN4Cats(kappa0=0.7, n=80, props=c(0.4, 0.4, 0.1, 0.1), alpha=0.05, raters=5);

Calculation of the Lowest Expected Value, kappaL, for a fixed sample size in a Study of Interobserver Agreement with a Multinomial Outcome (5 Levels)

Description

This function provides the potential lower bound for a 100(1 - \alpha) % confidence interval that can be calculated for a fixed sample size, n, and an anticipated value of \kappa, kappa0. This version assumes that the outcome of interest has five levels.

Usage

FixedN5Cats(kappa0, n, props, raters=2, alpha=0.05)

Arguments

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 \kappa, 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

Author(s)

Michael Rotondi, mrotondi@yorku.ca

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=0.6 assuming he has access to 150 subjects and 2 raters.  Further suppose that 
the prevalence of the traits of interest are 0.4, 0.2, 0.2, 0.1, 0.1.
## End(Not run)
FixedN5Cats(kappa0=0.6, n=150, props=c(0.4, 0.2, 0.2, 0.1, 0.1), alpha=0.05, raters=2);

Calculation of the Lowest Expected Value, kappaL, for a fixed sample size in a Study of Interobserver Agreement with a Binary Outcome

Description

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

Usage

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

Arguments

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 \kappa, 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

Author(s)

Michael Rotondi, mrotondi@yorku.ca

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);

Power-Based Approach for the Number of Subjects Required for a Study of Interobserver Agreement with Three Outcome Categories

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. This version assumes that the outcome is multinomial with three levels.

Usage

Power3Cats(kappa0, kappa1, props, raters=2, alpha=0.05, power=0.80)

Arguments

Details

This function provides detailed sample size estimation tools for studies of interobserver agreement with three levels. 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.

Value

Author(s)

Michael Rotondi, mrotondi@yorku.ca

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.

See Also

CI3Cats

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 categories is 
0.30, 0.60 and 0.10.
## End(Not run)
Power3Cats(kappa0=0.4, kappa1=0.6, props=c(0.30, 0.60, 0.10), alpha=0.05, power=0.80);

Power-Based Approach for the Number of Subjects Required for a Study of Interobserver Agreement with Four Outcome Categories

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. This version assumes that the outcome is multinomial with four levels.

Usage

Power4Cats(kappa0, kappa1, props, raters=2, alpha=0.05, power=0.80)

Arguments

Details

This function provides detailed sample size estimation tools for studies of interobserver agreement with four levels. 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.

Value

Author(s)

Michael Rotondi, mrotondi@yorku.ca

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.

See Also

CI4Cats

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 categories is 
0.30, 0.30, 0.30 and 0.10.
## End(Not run)
Power4Cats(kappa0=0.4, kappa1=0.6, props=c(0.30, 0.30, 0.30, 0.10), alpha=0.05, power=0.80);

Power-Based Approach for the Number of Subjects Required for a Study of Interobserver Agreement with Five Outcome Categories

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. This version assumes that the outcome is multinomial with five levels.

Usage

Power5Cats(kappa0, kappa1, props, raters=2, alpha=0.05, power=0.80)

Arguments

Details

This function provides detailed sample size estimation tools for studies of interobserver agreement with five levels. 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.

Value

Author(s)

Michael Rotondi, mrotondi@yorku.ca

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.

See Also

CI5Cats

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 categories is 
0.30, 0.20, 0.10, 0.30 and 0.10.
## End(Not run)
Power5Cats(kappa0=0.4, kappa1=0.6, props=c(0.30, 0.20, 0.10, 0.30, 0.10), alpha=0.05, power=0.80);

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

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.

Value

Author(s)

Michael Rotondi, mrotondi@yorku.ca

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.

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.
## End(Not run)
PowerBinary(kappa0=0.4, kappa1=0.6, props=0.30, alpha=0.05, power=0.80);