ab: Test/Power calculation for mediating effect

In gap: Genetic Analysis Package

Test/Power calculation for mediating effect

Description

Test/Power calculation for mediating effect

Usage

ab(
  type = "power",
  n = 25000,
  a = 0.15,
  sa = 0.01,
  b = log(1.19),
  sb = 0.01,
  alpha = 0.05,
  fold = 1
)

Arguments

type	string option: "test", "power".
n	default sample size to be used for power calculation.
a	regression coefficient from indepdendent variable to mediator.
sa	SE(a).
b	regression coefficient from mediator variable to outcome.
sb	SE(b).
alpha	size of siginficance test for power calculation.
fold	fold change for power calculation, as appropriate for a range of sample sizes.

Details

This function tests for or obtains power of mediating effect based on estimates of two regression coefficients and their standard errors. Note that for binary outcome or mediator, one should use log-odds ratio and its standard error.

Value

The returned value are z-test and significance level for significant testing or sample size/power for a given fold change of the default sample size.

Author(s)

Jing Hua Zhao

References

\insertRef

freathy08gap

Kline RB. Principles and practice of structural equation modeling, Second Edition. The Guilford Press 2005.

MacKinnon DP. Introduction to Statistical Mediation Analysis. Taylor & Francis Group 2008.

Preacher KJ, Leonardelli GJ. Calculation for the Sobel Test-An interactive calculation tool for mediation tests https://quantpsy.org/sobel/sobel.htm

See Also

ccsize

Examples

## Not run: 
ab()
n <- power <- vector()
for (j in 1:10)
{
   z <- ab(fold=j*0.01)
   n[j] <- z[1]
   power[j] <- z[2]
}
plot(n,power,xlab="Sample size",ylab="Power")
title("SNP-BMI-T2D association in EPIC-Norfolk study")

## End(Not run)

gap documentation built on Sept. 11, 2024, 5:36 p.m.