View source: R/logistic_implementation.R
logistic_power | R Documentation |
Simulate a p-value computation for logistic regression many times and compute the power. The design matrix is regenerated for each simulation.
logistic_power(nsims, n, p, groups, epsilon, effect_size, M, theta_0, alpha)
nsims |
Number of simulations. |
n |
Number of observations (number of rows of the design matrix) |
p |
Number of parameters (number of columns of the design matrix). Includes the intercept. |
groups |
A vector with the group number of each observation. |
epsilon |
The privacy parameter. |
effect_size |
The quotient of the parameter of interest (beta) and the standard deviation of the noise (sigma). |
M |
The number of subsamples when computing p-value. |
theta_0 |
The threshold. |
alpha |
The significance level. |
Will return a vector of p-values.
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