fastpos (version 0.4.1)

find_critical_pos: Find the critical point of stability

Description

Run simulations for one or several population correlations and return the critical points of stability (POS). The critical point of stability is the sample size at which a certain percentage of studies will fall into an a priori specified interval and stay in this interval if the sample size is increased further.

Usage

find_critical_pos(
  rhos,
  precision = 0.1,
  precision_rel = FALSE,
  sample_size_min = 20,
  sample_size_max = 1000,
  replace = TRUE,
  n_studies = 10000,
  confidence_levels = c(0.8, 0.9, 0.95),
  pop_size = 1e+06,
  n_cores = 1
)

Value

A data frame containing all the above information, as well as the points of stability.

Arguments

rhos

Vector of population correlations (can also be a single correlation).

precision

Precision around the correlation which is acceptable (defaults to 0.1). The precision will determine the corridor of stability which is just rho+-precision.

precision_rel

Whether the precision is absolute (rho+-precision or relative rho+-rho*precision), boolean (defaults to FALSE).

sample_size_min

Minimum sample size for each study (defaults to 20).

sample_size_max

Maximum sample size for each study (defaults to 1e3).

replace

Whether drawing samples is with replacement or not.

n_studies

Number of studies to run for each rho (defaults to 10e3).

confidence_levels

Confidence levels for point of stability. This corresponds to the quantile of the distribution of all found critical sample sizes (defaults to c(.8, .9, .95)).

pop_size

Population size (defaults to 1e6).

n_cores

Number of cores to use for simulation.

Examples

find_critical_pos(rhos = 0.5)
find_critical_pos(rhos = c(0.4, 0.5), n_studies = 1e3)