---
title: "Adding indices and computing reliability estimates"
date: "`r Sys.Date()`"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Indices and reliability estimates}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

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

Tidycomm provides a workflow to quickly add mean/sum indices of several variables to the dataset and compute reliability estimates for those added indices:

- `add_index()` adds a mean or sum index of the specified variables
- `get_reliability()` computes reliability estimates for all added indices

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

Once again, we will again sample data from the [Worlds of Journalism](https://worldsofjournalism.org/) 2012-16 study for demonstration purposes.  

```{r}
WoJ
```

`ethics_1` to `ethics_4` measure agreement with statements concerning ethics in journalism and may be combined into an index of 'ethical flexbility', while the items starting with `trust_` measure trust in various political institutions and thus may be combined into an index of trust in politics.

## Add mean and sum indices

`add_index()` adds a mean index of specified variables to the data. The second (or first, if used in a pipe) argument is the name of index variable to be created:

```{r}
WoJ %>% 
  add_index(ethical_flexibility, ethics_1, ethics_2, ethics_3, ethics_4) %>%
  # Select variables of relevance for output
  dplyr::select(ethical_flexibility, ethics_1, ethics_2, ethics_3, ethics_4)
```

To create a sum index instead, set `type = "sum"`:

```{r}
WoJ %>% 
  add_index(ethical_flexibility, ethics_1, ethics_2, ethics_3, ethics_4, type = "sum") %>%
  # Select variables of relevance for output
  dplyr::select(ethical_flexibility, ethics_1, ethics_2, ethics_3, ethics_4)
```

## Compute reliability estimates of created indices

Use `get_reliability()` to compute reliability/internal consistency estimates for indices created with `add_index()`. Passing no further arguments to the function will automatically compute reliability estimates for all indices created with `add_index()` found in the data and output Cronbach's $\alpha$ along with descriptives and index information.

```{r}
# Add two indices to data
WoJ <- WoJ %>% 
  add_index(ethical_flexibility, ethics_1, ethics_2, ethics_3, ethics_4) %>%
  add_index(trust_in_politics, trust_parliament, trust_government, trust_parties, trust_politicians)

WoJ %>% 
  get_reliability()
```

If you only want reliability estimates for specific indices, pass their names as function arguments.

```{r}
WoJ %>% 
  get_reliability(trust_in_politics)
```

Essentially, `get_reliability()` provides a wrapper for [the ci.reliability function from the MBESS package](https://cran.r-project.org/package=MBESS). Thus, all arguments of `MBESS::ci.reliability()` can be passed to `get_reliability()`. For example, to output  $\omega$ instead of Cronbach's $\alpha$ including robust maximum likelihood confidence intervals, you can type:

```{r}
WoJ %>% 
  get_reliability(type = 'omega', interval.type = 'mlr')
```

See the [function documentation](https://cran.r-project.org/package=MBESS) for more info (and don't forget to cite the `MBESS` package if using `get_reliability()`).