README.Rmd

---
output: github_document
---

<img src='logo/Hex.png' align="right" height="139" />

```{r setup, include=FALSE}
library(knitr)

opts_chunk$set(echo = TRUE, message = FALSE, warning = FALSE)

extract_pkgs <- function(fl) {
  if (length(fl) == 1) {
    txt <- read.delim(fl, header = FALSE)[[1]] |> 
      paste0(collapse = "\n")
    
    pkg_lib <- stringr::str_extract_all(txt, pattern = "(?<=library\\().{1,}?(?=\\))")
    
    pkg_req <- stringr::str_extract_all(txt, pattern = "(?<=require\\().{1,}?(?=\\))")
    
    pkg_name <- stringr::str_extract_all(txt, pattern = "[a-z|A-Z|0-9]{1,}(?=\\:\\:)")
    
    pkgs <- c(pkg_lib, pkg_req, pkg_name)
    
  } else if (length(fl) > 1) {
    pkgs <- sapply(fl, extract_pkgs)
  }
  
  pkgs |>
    unlist(recursive = TRUE) |> 
    as.vector() |> 
    unique()
}

make_pkg_table <- function(pkgs) {
  # pkgs <- pkgs[sapply(pkgs, function(x) length(x) > 0)]
  
  new_pkgs <- lapply(seq_along(pkgs), function(i) {
    lesson_pkgs <- pkgs[[i]]
    prev_lesson_pkgs <- unlist(head(pkgs,i-1))
    
    !lesson_pkgs %in% prev_lesson_pkgs
  })
  
  
  ps <- sapply(seq_along(pkgs), function(idx) {
    x <- pkgs[[idx]]
    is_new <- ifelse(new_pkgs[[idx]], "**", "")
    paste0(
      glue::glue("[{is_new}`{x}`{is_new}](https://CRAN.R-project.org/package={x})"),
      collapse = ", "
    )
  })
  
  c("|Lesson|Packages|\n|----|----|\n", # header
    glue::glue("|[{folder}](/{folder})|{ps}|\n\n",
             folder = names(pkgs))) |> 
    paste0(collapse = "")
}

get_src <- function(pkg) {
  pd <- packageDescription(pkg)
  if (is.null(src <- pd$Repository)) {
    if (!is.null(src <- pd$GithubRepo)) {
      src <- paste0("Github: ",pd$GithubUsername,"/",src)
    } else {
      src <- "Local version"
    }
  }
  return(src)
}
```

# Analysis of Factorial Designs foR Psychologists

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[![](https://img.shields.io/badge/Language-R-blue)](http://cran.r-project.org/)

<sub>*Last updated `r Sys.Date()`.*</sub>

This Github repo contains all lesson files for *Analysis of Factorial Designs foR Psychologists*. The goal is to impart students with the basic tools to fit and evaluate **statistical models for factorial designs (w/ plots) using [`afex`](https://afex.singmann.science/)**, and and conduct **follow-up analyses (simple effects, planned contrasts, post-hoc test; w/ plots) using [`emmeans`](https://cran.r-project.org/package=emmeans)**. Although the focus is on ANOVAs, the materials regarding follow-up analyses (\~80\% of the course) are applicable to linear mixed models, and even regression with factorial predictors.

These topics were taught in the graduate-level course ***Analyses of Variance*** (Psych Dep., Ben-Gurion University of the Negev, *Spring, 2019*). This course assumes basic competence in R (importing, regression modeling, plotting, etc.), along the lines of [*Practical Applications in R for Psychologists*](https://github.com/mattansb/Practical-Applications-in-R-for-Psychologists).


**Notes:**  

- This repo contains only materials relating to *Practical Applications in R*, and does not contain any theoretical or introductory materials.  
- Please note that some code does not work *on purpose*, to force students to learn to debug.

## Setup


You will need:

1. A fresh installation of [**`R`**](https://cran.r-project.org/) (preferably version 4.1 or above).
2. [RStudio IDE](https://www.rstudio.com/products/rstudio/download/) (optional, but recommended).
3. The following packages, listed by lesson:

```{r, echo=FALSE}
r_list <- list.files(pattern = ".(R|r)$", recursive = TRUE, full.names = TRUE) |> 
  Filter(f = \(x) !stringr::str_detect(x, pattern = "(SOLUTION|logo)"))

lesson_names <- stringr::str_extract(r_list, pattern = "(?<=(/)).{1,}(?=(/))")

r_list <- split(r_list, lesson_names)

pkgs <- lapply(r_list, extract_pkgs)

print_pkgs <- make_pkg_table(pkgs)
```

`r print_pkgs`

<sub>*(Bold denotes the first lesson in which the package was used.)*</sub>

You can install all the packages used by running:

```{r echo=FALSE, comment = "", warning=FALSE}
unique_pkgs <- pkgs |> 
  unlist(recursive = TRUE) |> 
  unique() |> sort()

packinfo <- installed.packages(fields = c("Package", "Version"))
V <- packinfo[unique_pkgs,"Version"]
src <- sapply(unique_pkgs, get_src)

cat("# in alphabetical order:")

cat("pkgs <-", dput(unique_pkgs) |> capture.output(), fill = 80) |> 
  capture.output() |> 
  styler::style_text()

cat('install.packages(pkgs, repos = c("https://easystats.r-universe.dev", getOption("repos")))')
```

<details>
<summary><i>Package Versions</i></summary>

Run on `r osVersion`, with R version `r packageVersion("base")`.

The packages used here:

```{r, echo=FALSE}
v_info <- paste0(glue::glue(" - `{unique_pkgs}` {V} (*{src}*)"), collapse = "\n")
```

`r v_info`

</details>