statsExpressions (version 1.2.0)

one_sample_test: One-sample tests

Description

A dataframe containing results from a one-sample test.

Usage

one_sample_test(
  data,
  x,
  type = "parametric",
  test.value = 0,
  alternative = "two.sided",
  k = 2L,
  conf.level = 0.95,
  tr = 0.2,
  bf.prior = 0.707,
  effsize.type = "g",
  top.text = NULL,
  ...
)

Arguments

data

A dataframe (or a tibble) from which variables specified are to be taken. Other data types (e.g., matrix,table, array, etc.) will not be accepted.

x

A numeric variable from the dataframe data.

type

A character specifying the type of statistical approach:

• "parametric"

• "nonparametric"

• "robust"

• "bayes"

You can specify just the initial letter.

test.value

A number indicating the true value of the mean (Default: 0).

alternative

a character string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater" or "less". You can specify just the initial letter.

k

Number of digits after decimal point (should be an integer) (Default: k = 2L).

conf.level

Scalar between 0 and 1. If unspecified, the defaults return 95% confidence/credible intervals (0.95).

tr

Trim level for the mean when carrying out robust tests. In case of an error, try reducing the value of tr, which is by default set to 0.2. Lowering the value might help.

bf.prior

A number between 0.5 and 2 (default 0.707), the prior width to use in calculating Bayes factors and posterior estimates. In addition to numeric arguments, several named values are also recognized: "medium", "wide", and "ultrawide", corresponding to r scale values of 1/2, sqrt(2)/2, and 1, respectively. In case of an ANOVA, this value corresponds to scale for fixed effects.

effsize.type

Type of effect size needed for parametric tests. The argument can be "d" (for Cohen's d) or "g" (for Hedge's g).

top.text

Text to display on top of the Bayes Factor message. This is mostly relevant in the context of ggstatsplot package functions.

...

Currently ignored.

Details

The exact test and the effect size details contained will depend on the type argument.

Internal function .f used to carry out statistical test:

• parametric: stats::t.test

• nonparametric: stats::wilcox.test

• robust: WRS2::trimcibt

• bayes: BayesFactor::ttestBF

Internal function .f.es used to compute effect size:

• parametric: effectsize::cohens_d, effectsize::hedges_g

• nonparametric: effectsize::rank_biserial

• robust: WRS2::trimcibt

• bayes: bayestestR::describe_posterior

For more, see- https://indrajeetpatil.github.io/statsExpressions/articles/stats_details.html

Examples

# NOT RUN {
# for reproducibility
set.seed(123)
library(statsExpressions)
options(tibble.width = Inf, pillar.bold = TRUE, pillar.neg = TRUE)

# ----------------------- parametric ---------------------------------------

one_sample_test(
  data = ggplot2::msleep,
  x = brainwt,
  test.value = 0.275,
  type = "parametric"
)

# ----------------------- non-parametric -----------------------------------

one_sample_test(
  data = ggplot2::msleep,
  x = brainwt,
  test.value = 0.275,
  type = "nonparametric"
)

# ----------------------- robust --------------------------------------------

one_sample_test(
  data = ggplot2::msleep,
  x = brainwt,
  test.value = 0.275,
  type = "robust"
)

# ---------------------------- Bayesian -----------------------------------

one_sample_test(
  data = ggplot2::msleep,
  x = brainwt,
  test.value = 0.275,
  type = "bayes",
  bf.prior = 0.8
)
# }