power.paired.prop {biostats101} | R Documentation |
Calculate the Power and Sample Size for Paired Proportions.
Description
This function calculates either the power given the sample size or the sample size given the power for paired proportions p1 and p2.
Usage
power.paired.prop(
p1,
p2,
n = NULL,
power = NULL,
conf.level = 0.95,
alternative = "two.sided"
)
Arguments
p1 |
Numeric, the proportion at the first occasion. |
p2 |
Numeric, the proportion at the second occasion. |
n |
Numeric, the sample size. |
power |
Numeric, the desired power (1 - beta). Default is 0.8 when calculating sample size. |
conf.level |
Numeric, the confidence level (1 - alpha). Default is 0.95. |
alternative |
Character, the type of alternative hypothesis. Options are 'two.sided' (default) or 'one.sided'. |
Value
A list containing the sample size, power, confidence level, and alternative hypothesis.
References
McNemar, Q. (1947). Note on the sampling error of the difference between correlated proportions or percentages. Psychometrika, 12(2), 153-157. https://doi.org/10.1007/BF02295996. Connor, R. J. (1987). Sample size for testing differences in proportions for the paired-sample design. Biometrics, 207-211. https://doi.org/10.2307/2531961.
Examples
# Calculate the power given the sample size for paired proportions
power.paired.prop(p1 = 0.1, p2 = 0.15, n = 900)
# Calculate the sample size given the power for paired proportions
power.paired.prop(p1 = 0.15, p2 = 0.1, power = 0.8)