power.paired.prop: Calculate the Power and Sample Size for Paired Proportions.

In biostats101: Practical Functions for Biostatistics Beginners

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)

biostats101 documentation built on Sept. 13, 2024, 1:11 a.m.