pc_modulation_power_fast: Estimate power for differences between proportion conflict...

In CrumpLab/conflictPower: Simulation based power analysis for adaptive control designs

Estimate power for differences between proportion conflict effects using monte-carlo simulation

Description

Estimate power for differences between proportion conflict effects using monte-carlo simulation

Usage

pc_modulation_power_fast(
  subjects,
  design,
  A_mc_c_nmst,
  A_mc_nc_nmst,
  A_mnc_c_nmst,
  A_mnc_nc_nmst,
  B_mc_c_nmst,
  B_mc_nc_nmst,
  B_mnc_c_nmst,
  B_mnc_nc_nmst,
  num_sims = 1000,
  alpha = 0.05
)

Arguments

subjects	A number for the number of subjects in simulated experiment
design	A string set to "paired" or "between"
A_mc_c_nmst	A vector for mostly conflict (mc), conflict trials (c) containing the parameters for an ex-gaussian distribution, c(n, mu, sigma, tau), where n is the number of trials.
A_mc_nc_nmst	A vector for mostly conflict (mc), conflict trials (c) containing the parameters for an ex-gaussian distribution, c(n, mu, sigma, tau), where n is the number of trials.
A_mnc_c_nmst	A vector for mostly no-conflict (mnc), conflict trials (c) containing the parameters for an ex-gaussian distribution, c(n, mu, sigma, tau), where n is the number of trials.
A_mnc_nc_nmst	A vector for mostly no-conflict (mnc), conflict trials (c) containing the parameters for an ex-gaussian distribution, c(n, mu, sigma, tau), where n is the number of trials.
B_mc_c_nmst	A vector for mostly conflict (mc), conflict trials (c) containing the parameters for an ex-gaussian distribution, c(n, mu, sigma, tau), where n is the number of trials.
B_mc_nc_nmst	A vector for mostly conflict (mc), conflict trials (c) containing the parameters for an ex-gaussian distribution, c(n, mu, sigma, tau), where n is the number of trials.
B_mnc_c_nmst	A vector for mostly no-conflict (mnc), conflict trials (c) containing the parameters for an ex-gaussian distribution, c(n, mu, sigma, tau), where n is the number of trials.
B_mnc_nc_nmst	A vector for mostly no-conflict (mnc), conflict trials (c) containing the parameters for an ex-gaussian distribution, c(n, mu, sigma, tau), where n is the number of trials.
num_sims	A number, simulations to run
alpha	A number, alpha criterion

Details

This function uses monte-carlo simulation to determine statistical power associated for detecting a modulation to a proportion conflict effect, specifically a difference between two proportion conflict effects.

Power is the proportion of simulated experiments that return p-values less than the defined alpha criterion.

Value

A number, power: the proportion of simulated experiments that returned a p-value less than the alpha criterion for the conflict effect

Examples

pc_modulation_power_fast(subjects=20,
  design ="paired",
  A_mc_c_nmst = c(80,550,100,100),
  A_mc_nc_nmst = c(20,500,100,100),
  A_mnc_c_nmst = c(20,570,100,100),
  A_mnc_nc_nmst = c(80,500,100,100),
  B_mc_c_nmst = c(80,530,100,100),
  B_mc_nc_nmst = c(20,500,100,100),
  B_mnc_c_nmst = c(20,570,100,100),
  B_mnc_nc_nmst = c(80,500,100,100),
  num_sims = 1000,
  alpha = .05)

CrumpLab/conflictPower documentation built on May 17, 2022, 5:48 a.m.