pc_modulation_power_fast.Rd
Estimate power for differences between proportion conflict effects using monte-carlo simulation
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 )
subjects | A number for the number of subjects in simulated experiment |
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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 |
A number, power: the proportion of simulated experiments that returned a p-value less than the alpha criterion for the conflict effect
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.
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) #> [1] 0.218