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)

`%>%` <- dplyr::`%>%`
```

# Structural Equation Modeling foR Psychologists

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[![](https://img.shields.io/badge/CC-BY--NC%204.0-lightgray)](http://creativecommons.org/licenses/by-nc/4.0/)  
[![](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 *SEM - Practical Applications in R*. The goal is to impart students with the basic tools to construct, evaluate and compare **Structural Equation Models (SEM; w/ plots), using [`lavaan`](http://lavaan.ugent.be/)**.

These topics were taught in the graduate-level course ***Structural Equation Modeling*** (Psych Dep., Ben-Gurion University of the Negev). 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

```{r, echo=FALSE}
extract_pkgs <- function(fl) {
  `%>%` <- dplyr::`%>%`
  
  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) %>%
    unique()
}

make_pkg_table <- function(pkgs) {
  `%>%` <- dplyr::`%>%`
  
  pkgs <- pkgs[sapply(pkgs, function(x) length(x) > 0)]
  
  ps <- sapply(pkgs, function(x){
    paste0(
      glue::glue("[`{x}`](https://CRAN.R-project.org/package={x})"),
      collapse = ", "
    )
  })
  
  glue::glue("|[{folder}](/{folder})|{ps}|\n\n",
             folder = names(pkgs)) %>% 
    c("|Lesson|Packages|\n|----|----|\n", .) %>% # header
    paste0(collapse = "")
}
```


You will need:

1. A fresh installation of [**`R`**](https://cran.r-project.org/) (preferably version 4.0 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, message=FALSE, warning=FALSE}
r_list <- list.files(pattern = ".(R|r)$", recursive = TRUE, full.names = TRUE) %>% 
  .[!stringr::str_detect(., pattern = "(SOLUTION|logo)")] %>% 
  .[stringr::str_detect(., pattern = "^./[0-9]")]

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`

You can install all the packages used by running:

```{r echo=FALSE, comment = "", warning=FALSE}

pkgs <- pkgs %>% 
  unlist(recursive = TRUE) %>% 
  unique() %>% sort()

cat("# in alphabetical order:")

pkgs %>% {
  capture.output(dput(.))
} %>% {
  capture.output(cat("pkgs <-", ., fill = 80))
} %>%
  styler::style_text()

cat("install.packages(pkgs, dependencies = TRUE)")
```

<details>
<summary><i>Package Versions</i></summary>
The package versions used here:
```{r, echo=FALSE}
packinfo <- installed.packages(fields = c("Package", "Version"))

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 <- "Dev"
    }
  }
  return(src)
}

V <- packinfo[pkgs,"Version"]
src <- sapply(pkgs, get_src)
# setNames(paste0(V, " (", src,")"), pkgs)

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

`r v_info`

</details>


## Other Useful Resources

### Other Courses

In addition to [`lavaan`'s toutorials](http://lavaan.ugent.be/tutorial/index.html), you might find the following online courses useful: 

- Sacha Epskamp's [online course](http://sachaepskamp.com/SEM2020) and [YouTube lectures](https://www.youtube.com/playlist?list=PLliBbGBc5nn3m8bXQ4CmOep3UmQ_5tVlC).  
  - See also the [`psychonetrics`](http://psychonetrics.org/) package for psychometric network modeling.  
- Michael Hallquist's [course](https://psu-psychology.github.io/psy-597-SEM/).


### Selected Quantitude (podcast) Episods

These are selected episodes from the [Quantitude podcast](https://quantitudepod.org/) related to SEM:

- [S2E08: **Mediation** and the Art of Squid Spleening](https://www.buzzsprout.com/639103/5817541-s2e08-mediation-and-the-art-of-squid-spleening)
- [S2E24: The **Equivalent Models** Problem](https://www.buzzsprout.com/639103/7983649-s2e24-the-equivalent-models-problem)
- [S2E26: MLM vs. **SEM**: Opportunities for Growth](https://www.buzzsprout.com/639103/8084578-s2e26-mlm-vs-sem-opportunities-for-growth)