---
title: "Exploratory Factor Analysis Workflow"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Exploratory Factor Analysis Workflow}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

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

# Exploratory Factor Analysis Workflow

This vignette shows a compact screening-to-EFA workflow with the example ordinal
dataset included in `PsychoMatic`.

```{r setup}
library(PsychoMatic)
data(psychomatic_ordinal)
```

## Item Screening

```{r item-screening}
screen_items(psychomatic_ordinal)
```

## Reverse Scoring And Scale Scores

If an item is theoretically reverse keyed, reverse it before computing scale
scores.

```{r scoring}
scored <- score_scale(
  psychomatic_ordinal,
  items = names(psychomatic_ordinal),
  method = "mean",
  min_valid = 0.80
)
scored$reliability
```

## Exploratory Factor Analysis

The full automated EFA routine can be run as follows. It is not evaluated during
CRAN vignette checks because parallel analysis and polychoric correlations may
take longer on constrained machines.

```{r efa-auto, eval = FALSE}
efa_result <- efa_auto(
  psychomatic_ordinal,
  rotation = "oblique",
  max_iter = 3,
  verbose = FALSE,
  language = "eng"
)
summary(efa_result)
```