statsExpressions (version 0.6.2)

expr_anova_parametric: Expression containing parametric ANOVA results

Description

The effect sizes and their confidence intervals are computed using effectsize::eta_squared and effectsize::omega_squared functions.

Usage

expr_anova_parametric(
  data,
  x,
  y,
  subject.id = NULL,
  paired = FALSE,
  k = 2L,
  conf.level = 0.95,
  effsize.type = "omega",
  var.equal = FALSE,
  output = "expression",
  ...
)

Arguments

data

A dataframe (or a tibble) from which variables specified are to be taken. A matrix or tables will not be accepted.

x

The grouping variable from the dataframe data.

y

The response (a.k.a. outcome or dependent) variable from the dataframe data.

subject.id

In case of repeated measures design (paired = TRUE, i.e.), this argument specifies the subject or repeated measures id. Note that if this argument is NULL (which is the default), the function assumes that the data has already been sorted by such an id by the user and creates an internal identifier. So if your data is not sorted and you leave this argument unspecified, the results can be inaccurate.

paired

Logical that decides whether the experimental design is repeated measures/within-subjects or between-subjects. The default is FALSE.

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).

effsize.type

Type of effect size needed for parametric tests. The argument can be "eta" (partial eta-squared) or "omega" (partial omega-squared).

var.equal

a logical variable indicating whether to treat the variances in the samples as equal. If TRUE, then a simple F test for the equality of means in a one-way analysis of variance is performed. If FALSE, an approximate method of Welch (1951) is used, which generalizes the commonly known 2-sample Welch test to the case of arbitrarily many samples.

output

If "expression", will return expression with statistical details, while "dataframe" will return a dataframe containing the results.

...

Additional arguments (currently ignored).

Value

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

Examples

# NOT RUN {
# for reproducibility
set.seed(123)
library(statsExpressions)

# -------------------- between-subjects ------------------------------

# to get expression
expr_anova_parametric(
  data = ggplot2::msleep,
  x = vore,
  y = sleep_rem
)

# -------------------- repeated measures ------------------------------

# to get dataframe
expr_anova_parametric(
  data = iris_long,
  x = condition,
  y = value,
  subject.id = id,
  paired = TRUE,
  output = "dataframe"
)
# }