simitation (version 0.0.7)

simstudy.chisq.test.gf: simstudy.chisq.test.gf

Description

simstudy.chisq.test.gf

Usage

simstudy.chisq.test.gf(
  n,
  values,
  actual.probs,
  hypothesized.probs = NULL,
  num.experiments = 1,
  conf.level = 0.95,
  correct = TRUE,
  the.quantiles = c(0.025, 0.1, 0.25, 0.5, 0.75, 0.9, 0.975),
  experiment.name = "experiment",
  value.name = "x",
  seed = 7261,
  vstr = 3.6
)

Value

A list containing three elements: 'simdat': A data frame of the simulated data based on chi-squared distributions. 'test.statistics': A data frame or data.table containing the results of chi-squared tests performed on the simulated data. 'sim.analysis': Summary statistics or analysis results from the simulated chi-squared tests.

Arguments

n

A numeric value for the number of observations in each experiment.

values

A vector of values specifying the sample space.

actual.probs

A vector of probabilities used to simulate the values.

hypothesized.probs

A vector of hypothesized probabilities for the values.

num.experiments

A numeric value representing the number of simulated experiments.

conf.level

A numeric value between 0 and 1 representing the confidence level (1 - significance level).

correct

See help(chisq.test).

the.quantiles

A numeric vector of values between 0 and 1. Summary statistics to analyze the tests will return the specified quantiles.

experiment.name

A character value providing the name for the column identifying the experiment.

value.name

A character value providing the name for the simulated values.

seed

A single numeric value, interpreted as an integer, or NULL. See help(set.seed).

vstr

A character string containing a version number, e.g., "1.6.2". The default RNG configuration of the current R version is used if vstr is greater than the current version. See help(set.seed).

Examples

study.chisq.gf <- simstudy.chisq.test.gf(n = 75, values = LETTERS[1:4],
actual.probs = c(0.3, 0.3, 0.2, 0.2),
hypothesized.probs = rep.int(x = 0.25, times = 4),
num.experiments = 2, conf.level = 0.95, correct = FALSE,
the.quantiles = c(0.25, 0.75), experiment.name = "experiment_id",
value.name = "classification", seed = 61)