singcar (version 0.1.5)

BTD_cov_power: Power calculator for BTD_cov

Description

Computationally intense. Lower iter and/or nsim for less exact but faster calculations. Calculates approximate power, given sample size, using Monte Carlo simulation for the Bayesian test of deficit with covariates for specified (expected) case score, means and standard deviations for the control sample on the task of interest and included covariates. The number of covariates defaults to 1, means and standard deviations for the task and covariate defaults to 0 and 1, so if no other values are given the case score is interpreted as deviation from the mean in standard deviations for both task and covariate.

Usage

BTD_cov_power(
  case,
  case_cov,
  control_task = c(0, 1),
  control_covar = c(0, 1),
  cor_mat = diag(2) + 0.3 - diag(c(0.3, 0.3)),
  sample_size,
  alternative = c("less", "greater", "two.sided"),
  alpha = 0.05,
  nsim = 1000,
  iter = 1000
)

Value

Returns a single value approximating the power of the test for the given parameters.

Arguments

case

A single value from the expected case observation on the task of interest.

case_cov

A vector of expected case observations from covariates of interest.

control_task

A vector of length 2 containing the expected mean and standard deviation of the task of interest. In that order.

control_covar

A matrix with 2 columns containing expected means (in the 1st column) and standard deviations (in the 2nd column) of the included covariates.

cor_mat

A correlation matrix containing the correlations of the task of interest and the coviariate(s). The first variable is treated as the task of interest. Defaults to a correlation of 0.3 between the covariate and the variate of interest.

sample_size

Single value of the size of the sample for which you wish to calculate power.

alternative

The alternative hypothesis. A string of either "less" (default), "greater" or "two.sided".

alpha

The specified Type I error rate. This can also be varied, with effects on power.

nsim

The number of simulations for the power calculation. Defaults to 1000 due to BTD_cov already being computationally intense.

iter

The number of simulations used by the BTD_cov. Defaults to 1000.

Examples

cor_mat = matrix(c(1, 0.2, 0.3, 0.2, 1, 0.4, 0.3, 0.4, 1), ncol = 3)

BTD_cov_power(case = -2, case_cov = c(105, 30), control_task = c(0, 1),
control_covar = matrix(c(100, 40, 15, 10), ncol = 2), sample_size = 15,
cor_mat = cor_mat, iter = 20, nsim = 20)