analyze.simstudy.t {simitation}

analyze.simstudy.t

Description

analyze.simstudy.t

Usage

analyze.simstudy.t(
  test.statistics.t,
  alternative = c("two.sided", "less", "greater"),
  conf.level = 0.95,
  the.quantiles = c(0.025, 0.1, 0.25, 0.5, 0.75, 0.9, 0.975)
)

Arguments

test.statistics.t

Summary information for fitting one-sample t tests. Structure is in the form returned by the function simitation::sim.t.test().

alternative

See help(t.test).

conf.level

See help(t.test)

the.quantiles

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

Value

A list containing the following elements:

• estimate.summary: Summary statistics for the estimate.

• stat.summary: Summary statistics for the t-test statistic.

• p.value.summary: Data frame with proportions of tests that rejected and did not reject the null hypothesis.

• ci.range.summary: Summary statistics for the confidence interval range.

• ci.proportion.above.null.summary: Summary statistics for the proportion of the upper confidence limit above the null value.

• ci.proportion.below.null.summary: Summary statistics for the proportion of the lower confidence limit below the null value.

• ci.limit.summary: (Only if 'alternative' is "greater" or "less") Summary statistics for either the lower or upper confidence limit, depending on the specified alternative.

Examples

simdat.t <- sim.t(n = 25, mean = 0.3, sd = 1,  num.experiments = 2,
experiment.name = "experiment", value.name = "x", seed = 2187)


test.statistics.t <- sim.t.test(simdat.t = simdat.t, alternative = "greater",
 mu = 0, conf.level = 0.95, experiment.name = "experiment", value.name = "x")

analysis.t <- analyze.simstudy.t(test.statistics.t = test.statistics.t,
conf.level = 0.95, alternative = "greater", the.quantiles =
c(0.025, 0.25, 0.25, 0.5, 0.75, 0.975))