pwrss (version 1.3.1)

power.exact.onecor: Power Analysis for One-Sample Correlation (Exact)

Description

Calculates power, sample size, or minimum detectable correlation (only one can be NULL at a time) to test a (Pearson) correlation against a constant using exact method described in Barabesi and Greco (2002).

Formulas are validated using G*Power.

Usage

power.exact.onecor(
  rho = NULL,
  req.sign = "+",
  null.rho = 0,
  n = NULL,
  n.max = 10000,
  power = NULL,
  alpha = 0.05,
  alternative = c("two.sided", "one.sided"),
  verbose = 1,
  utf = FALSE
)

Value

parms

list of parameters used in calculation.

test

type of the statistical test (Z-Test)

rho.alpha

critical value(s).

es

minimum detectable correlation.

power

statistical power\((1-\beta)\).

n

sample size.

Arguments

rho

correlation.

req.sign

whether estimated rho is smaller or larger than the null.rho (when minimum detectable rho is of interest).

null.rho

correlation when null is true. Only 0 is allowed for now.

n

sample size.

n.max

max. number of observations in the sample (default: 500).

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; the direction or type of the hypothesis test: "two.sided" or "one.sided".

verbose

1 by default (returns test, hypotheses, and results), if 2 a more detailed output is given (plus key parameters and definitions), if 0 no output is printed on the console.

utf

logical; whether the output should show Unicode characters (if encoding allows for it). FALSE by default.

References

Barabesi, L., & Greco, L. (2002). A Note on the Exact Computation of the Student t, Snedecor F and Sample Correlation Coefficient Distribution Functions. Journal of the Royal Statistical Society. Series D (The Statistician), 51(1), 105–110. https://www.jstor.org/stable/3650394

Examples

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

# expected correlation is 0.20 and it is greater than 0
power.exact.onecor(rho = 0.20,
                   power = 0.80,
                   alpha = 0.05,
                   alternative = "one.sided")