singcar (version 0.1.2)

BTD_power: Power calculator for BTD

Description

Calculates approximate power, given sample size, using Monte Carlo simulation for the Bayesian test of deficit for a specified case score, mean and standard deviation for the control sample. The mean and standard deviation 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.

Usage

BTD_power(
  case,
  mean = 0,
  sd = 1,
  sample_size,
  alternative = c("less", "greater", "two.sided"),
  alpha = 0.05,
  nsim = 1000,
  iter = 1000
)

Arguments

case

A single value from the expected case observation.

mean

The expected mean of the control sample.

sd

The expected standard deviation of the control sample.

sample_size

The size of the control sample, vary this parameter to see how the sample size affects 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 already being computationally intense.

iter

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

Value

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

Examples

# NOT RUN {
BTD_power(case = -2, mean = 0, sd = 1, sample_size = 20)
# }