---
title: "Summarizing Results"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Summarizing Results}
  %\VignetteEngine{knitr::rmarkdown}
  \usepackage[utf8]{inputenc}
---

```{r setup, include=FALSE, message=FALSE, warning=FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  warning = FALSE,
  message = FALSE,
  fig.retina = 3,
  comment = "#>"
)
```

```{r, child='../man/rmdchunks/header.Rmd'}
```

# Extracting summary tables 

The most common function used to view an overall summary of a model is the `summary()` function:

```{r}
library(logitr)

model <- logitr(
  data    = yogurt,
  outcome = "choice",
  obsID   = "obsID",
  pars    = c("price", "feat", "brand")
)

summary(model)
```

The summary prints out a table of the model coefficients as well as other information about the model, such as the log-likelihood, the number of observations, etc.

You can extract the coefficient from the summary table as a `data.frame` using `coef(summary(model))`:

```{r}
coefs <- coef(summary(model))
coefs
```

## The {broom} package

Another approach for extracting the model coefficients as a data frame is to use the `tidy()` function from the [{broom}](https://broom.tidymodels.org/index.html) package:

```{r}
library(broom)

coefs <- tidy(model)
coefs
```

The `tidy()` function returns a `tibble` and provides a more standardized output and interfaces well with other packages. You can also append a confidence interval to the data frame:

```{r}
coefs <- tidy(model, conf.int = TRUE, conf.level = 0.95)
coefs
```

# Extracting other values 

You can also extract other values of interest at the solution, such as:

**The estimated coefficients**

```{r}
coef(model)
```

**The estimated standard errors**

```{r}
se(model)
```

**The log-likelihood**

```{r}
logLik(model)
```

**The variance-covariance matrix**

```{r}
vcov(model)
```

You can also view a summary of statistics about the model using the `glance()` function from the [{broom}](https://broom.tidymodels.org/index.html) package:

```{r}
glance(model)
```

# Formatted summary tables

## The {gtsummary} package

Often times you will need to create summary tables that are formatted for publication. The [{gtsummary}](https://www.danieldsjoberg.com/gtsummary/) package offers a convenient solution that works well with `logitr`models. For example, a formatted summary table can be obtained using the `tbl_regression()` function:

```{r}
library(gtsummary)

model |> 
  tbl_regression()
```

The `tbl_regression()` function has many [options](https://www.danieldsjoberg.com/gtsummary/articles/tbl_regression.html) for customizing the output table. For example, you can change the coefficient names with the `label` argument:

```{r}
model |> 
  tbl_regression(
    label = list(
        feat = "Newspaper ad shown?",
        brand = "Yogurt's brand"
    )
  )
```

The {gtsummary} package supports a wide variety of output types, including support for [LaTeX](https://www.latex-project.org/). One you create the table with `tbl_regression()`, you can print it a variety of ways. For example, once you've created a table `x`,

```{r, eval=FALSE}
x <- model |>
  tbl_regression()
```

you can print it to LaTeX with any of the following ways:

- `as_gt(x) |> gt::as_latex()`
- `as_kable_extra(x, format = "latex")`
- `as_hux_table(x) |> to_latex()`
- `as_kable(x, format = "latex")`

Multiple models can also be printed in the same table:

```{r}
model1 <- model

model2 <- logitr(
  data    = yogurt,
  outcome = "choice",
  obsID   = "obsID",
  pars    = c("price*feat", "brand")
)

# Make individual tables
t1 <- tbl_regression(model1)
t2 <- tbl_regression(model2)

# Merge tables
tbl_merge(
  tbls = list(t1, t2),
  tab_spanner = c("**Baseline**", "**Interaction**")
)
```

## The {texreg} package

Another option for obtaining a formatted table is to use the [{texreg}](https://github.com/leifeld/texreg) package. This is particularly useful for obtaining tables formatted for use in [LaTeX](https://www.latex-project.org/).

For example, you can print a summary to the screen using `screenreg()`:

```{r}
library(texreg)

screenreg(model, stars = c(0.01, 0.05, 0.1))
```

Likewise, you can print the LaTeX code for a summary table using `texreg()`

```{r}
library(texreg)

texreg(model, stars = c(0.01, 0.05, 0.1))
```

Similar to {gtsummary}, multiple models can be printed using `screenreg()` or `texreg()`:

```{r}
model1 <- model

model2 <- logitr(
  data    = yogurt,
  outcome = "choice",
  obsID   = "obsID",
  pars    = c("price*feat", "brand")
)

screenreg(
  list(
    model1,
    model2
  ),
  stars = c(0.01, 0.05, 0.1),
  custom.model.names = c("Baseline", "Interaction")
)
```