# subtitle_anova_parametric

##### Making text subtitle for parametric ANOVA.

Making text subtitle for parametric ANOVA.

##### Usage

```
subtitle_anova_parametric(data, x, y, paired = FALSE,
effsize.type = "unbiased", partial = TRUE, conf.level = 0.95,
nboot = 100, var.equal = FALSE, sphericity.correction = TRUE,
k = 2, stat.title = NULL, messages = TRUE, ...)
```

##### 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`

.- paired
Logical that decides whether the design is repeated measures/within-subjects (in which case one-way Friedman Rank Sum Test will be carried out) or between-subjects (in which case one-way Kruskal<U+2013>Wallis H test will be carried out). The default is

`FALSE`

.- effsize.type
Type of effect size needed for

*parametric*tests. The argument can be`"biased"`

(equivalent to`"d"`

for Cohen's*d*for**t-test**;`"partial_eta"`

for partial eta-squared for**anova**) or`"unbiased"`

(equivalent to`"g"`

Hedge's*g*for**t-test**;`"partial_omega"`

for partial omega-squared for**anova**)).- partial
Logical that decides if partial eta-squared or omega-squared are returned (Default:

`TRUE`

). If`FALSE`

, eta-squared or omega-squared will be returned. Valid only for objects of class`lm`

,`aov`

,`anova`

, or`aovlist`

.- conf.level
Scalar between 0 and 1. If unspecified, the defaults return

`95%`

lower and upper confidence intervals (`0.95`

).- nboot
Number of bootstrap samples for computing confidence interval for the effect size (Default:

`100`

).- 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.- sphericity.correction
Logical that decides whether to apply correction to account for violation of sphericity in a repeated measures design ANOVA (Default:

`TRUE`

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

`k = 2`

).- stat.title
A character describing the test being run, which will be added as a prefix in the subtitle. The default is

`NULL`

. An example of a`stat.title`

argument will be something like`"Student's t-test: "`

.- messages
Decides whether messages references, notes, and warnings are to be displayed (Default:

`TRUE`

).- ...
Additional arguments.

##### Note

For repeated measures designs (`paired = TRUE`

), only omega-squared and
partial eta-squared effect sizes are supported.

##### Examples

```
# NOT RUN {
# for reproducibility
set.seed(123)
library(ggstatsplot)
# -------------------- between-subjects ------------------------------
# with defaults
ggstatsplot::subtitle_anova_parametric(
data = ggplot2::msleep,
x = vore,
y = sleep_rem,
paired = FALSE,
k = 3
)
# modifying the defaults
ggstatsplot::subtitle_anova_parametric(
data = ggplot2::msleep,
x = vore,
y = sleep_rem,
paired = FALSE,
effsize.type = "biased",
partial = FALSE,
var.equal = TRUE,
nboot = 10
)
# -------------------- repeated measures ------------------------------
ggstatsplot::subtitle_anova_parametric(
data = iris_long,
x = condition,
y = value,
paired = TRUE,
k = 4,
nboot = 10
)
# }
```

*Documentation reproduced from package ggstatsplot, version 0.0.12, License: GPL-3 | file LICENSE*