--- title: "Test and effect size details" output: rmarkdown::html_vignette: toc: true toc_depth: 4 vignette: > %\VignetteIndexEntry{Test and effect size details} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} --- ```{r} #| label = "setup", #| message = FALSE, #| warning = FALSE, #| include = FALSE, #| echo = FALSE source("setup.R") ``` This vignette can be cited as: ```{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: ## References - For parametric and non-parametric effect sizes: - For robust effect sizes: - For Bayesian posterior estimates: ## Suggestions If you find any bugs or have any suggestions/remarks, please file an issue on GitHub: