1-One-Correlation: One Correlation against a Constant (One Sample z Test)

In pwrss: Statistical Power and Sample Size Calculation Tools

One Correlation against a Constant (One Sample z Test)

Description

Calculates statistical power or minimum required 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 G*Power and tables in PASS documentation.

Usage

pwrss.z.corr(r = 0.50, r0 = 0, alpha = 0.05,
             alternative = c("not equal","greater","less"),
             n = NULL, power = NULL, verbose = TRUE)

Arguments

r	expected correlation
r0	constant to be compared (a correlation)
n	sample size
power	statistical power (1-\beta)
alpha	probability of type I error
alternative	direction or type of the hypothesis test: "not equal", "greater", or "less"
verbose	if FALSE no output is printed on the console

Value

parms	list of parameters used in calculation
test	type of the statistical test (z test)
ncp	non-centrality parameter
power	statistical power (1-\beta)
n	sample size

References

Bulus, M., & Polat, C. (in press). pwrss R paketi ile istatistiksel guc analizi [Statistical power analysis with pwrss R package]. Ahi Evran Universitesi Kirsehir Egitim Fakultesi Dergisi. https://osf.io/ua5fc/download/

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
pwrss.z.corr(r = 0.20, r0 = 0,
             alpha = 0.05, power = 0.80,
             alternative = "not equal")

# expected correlation is 0.20 and it is greater than 0.10
pwrss.z.corr(r = 0.20, r0 = 0.10,
             alpha = 0.05, power = 0.80,
             alternative = "greater")

pwrss documentation built on April 12, 2023, 12:34 p.m.