Test and effect size details

#| label = "setup",
#| message = FALSE,
#| warning = FALSE,
#| include = FALSE,
#| echo = FALSE
source("setup.R")

This vignette can be cited as:

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


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()


oneway_anova()


two_sample_test()


one_sample_test()


corr_test()


contingency_table()


meta_analysis()


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

References

Suggestions

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



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statsExpressions documentation built on Sept. 12, 2023, 5:07 p.m.