---
title: "Test and effect size details"
author: "Indrajeet Patil"
date: "`r Sys.Date()`"
output:
  rmarkdown::html_vignette:
    fig_width: 6
    fig.align: 'center'
    fig.asp: 0.618
    dpi: 300
    toc: true
    toc_depth: 4
vignette: >
  %\VignetteIndexEntry{Test and effect size details}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r setup, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  warning = FALSE,
  message = FALSE
)
```

```{r citation, echo=FALSE, comment = ""}
citation("statsExpressions")
```

## Introduction

Here a go-to summary about statistical test carried out and the returned effect
size for each function is provided. This should be useful if one needs to find
out more information about how an argument is resolved in the underlying package
or if one wishes to browse the source code. So, for example, if you want to know
more about how one-way (between-subjects) ANOVA, you can run
`?stats::oneway.test` in your R console.

Abbreviations used: CI = Confidence Interval

## Summary of functionality

```{r child="../man/rmd-fragments/functionality.Rmd"}

```

## Summary of tests and effect sizes

Here a go-to summary about statistical test carried out and the returned effect
size for each function is provided. This should be useful if one needs to find
out more information about how an argument is resolved in the underlying package
or if one wishes to browse the source code. So, for example, if you want to know
more about how one-way (between-subjects) ANOVA, you can run
`?stats::oneway.test` in your R console.

### `centrality_description`

```{r child="../man/rmd-fragments/centrality_description.Rmd"}

```

### `oneway_anova`

```{r child="../man/rmd-fragments/oneway_anova.Rmd"}

```

### `two_sample_test` 

```{r child="../man/rmd-fragments/two_sample_test.Rmd"}

```

### `one_sample_test`

```{r child="../man/rmd-fragments/one_sample_test.Rmd"}

```

### `corr_test`

```{r child="../man/rmd-fragments/corr_test.Rmd"}

```

### `contingency_table`

```{r child="../man/rmd-fragments/contingency_table.Rmd"}

```

### `meta_analysis`

```{r child="../man/rmd-fragments/meta_analysis.Rmd"}

```

## Effect size interpretation

See `effectsize`'s interpretation functions to check different rules/conventions
to interpret effect sizes:

<https://easystats.github.io/effectsize/reference/index.html#section-interpretation>

## Dataframe as output

Although the primary focus of this package is to get expressions containing
statistical results, one can also use it to extract dataframes containing these
details. 

For a more detailed summary of these dataframe:
<https://indrajeetpatil.github.io/statsExpressions//articles/web_only/dataframe_outputs.html>

## References

  - For parametric and non-parametric effect sizes:
    <https://easystats.github.io/effectsize/articles/simple_htests.html>

  - For robust effect sizes:
    <https://CRAN.R-project.org/package=WRS2/vignettes/WRS2.pdf>

  - For Bayesian posterior estimates:
    <https://easystats.github.io/bayestestR/articles/bayes_factors.html>

## Suggestions

If you find any bugs or have any suggestions/remarks, please file an issue on GitHub: 
<https://github.com/IndrajeetPatil/statsExpressions/issues>
