correlations.one: Power Analysis for One-Sample Correlation

In pwrss: Statistical Power and Sample Size Calculation Tools

Power Analysis for One-Sample Correlation

Description

Calculates power or sample size (only one can be NULL at a time) to test a (Pearson) correlation against a constant using Fisher's z transformation.

Formulas are validated using PASS and G*Power.

Usage

power.z.onecor(rho, null.rho = 0,
               n = NULL, power = NULL, alpha = 0.05,
               alternative = c("two.sided", "one.sided"),
               ceiling = TRUE, verbose = TRUE, pretty = FALSE)

Arguments

rho	correlation.
null.rho	correlation when null is true.
n	sample size.
power	statistical power, defined as the probability of correctly rejecting a false null hypothesis, denoted as 1 - \beta.
alpha	type 1 error rate, defined as the probability of incorrectly rejecting a true null hypothesis, denoted as \alpha.
alternative	character; direction or type of the hypothesis test: "two.sided" or "one.sided".
ceiling	logical; whether sample size should be rounded up. TRUE by default.
verbose	logical; whether the output should be printed on the console. TRUE by default.
pretty	logical; whether the output should show Unicode characters (if encoding allows for it). FALSE by default.

Value

parms	list of parameters used in calculation.
test	type of the statistical test (Z-Test)
mean	mean of the alternative distribution.
sd	standard deviation of the alternative distribution.
null.mean	mean of the null distribution.
null.sd	standard deviation of the null distribution.
z.alpha	critical value(s).
power	statistical power (1-\beta).
n	sample size.

References

Bulus, M., & Polat, C. (2023). pwrss R paketi ile istatistiksel guc analizi [Statistical power analysis with pwrss R package]. Ahi Evran Universitesi Kirsehir Egitim Fakultesi Dergisi, 24(3), 2207-2328. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.29299/kefad.1209913")}

Chow, S. C., Shao, J., Wang, H., & Lokhnygina, Y. (2018). Sample size calculations in clinical research (3rd ed.). Taylor & Francis/CRC.

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates.

Examples

# expected correlation is 0.20 and it is different from 0
# it could be 0.20 as well as -0.20
power.z.onecor(rho = 0.20,
               power = 0.80,
               alpha = 0.05,
               alternative = "two.sided")

# expected correlation is 0.20 and it is greater than 0.10
power.z.onecor(rho = 0.20, null = 0.10,
               power = 0.80,
               alpha = 0.05,
               alternative = "one.sided")

pwrss documentation built on Sept. 16, 2025, 9:11 a.m.