# A unified syntax for accessing models’ information

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The richness and variety of packages for building and fitting statistical models in R is absolutely astonishing and contributes to the language’s popularity. However, **this diversity makes it hard for developpers** that want to create tools that work with different types of models. Indeed, the way to access models’ internal information (such as **parameters names**, **formulae**, **data**, etc.) is **not unified**, forcing the developers to spend some time figuring out how to do it for each model type.

**This time is over!**

## Insight

Recently, we have decided to collaborate around the new easystats project, a set of packages designed to make your life easier (currently very work in progress). However, in order to create these packages and functions, **we needed a basis**, a stable cornerstone, that would allow the unified way of accessing models information.

And ** insight** was born.

The goal of insight is to provide tools to help an **easy, intuitive and consistent accesss** to information contained in various models. Indeed, although there are generic functions to get information and data from models, many modelling-functions from different packages do not provide such methods to access these information. The insight package aims at closing this gap by providing functions that work for (almost) any model.

`insight`

can be installed as follows:

install.packages("insight") # Install from CRAN library(insight) # Load the package

## Example

Let’s see how it works on a very simple regression model:

model <- lm(Sepal.Length ~ Species, data=iris)

- Find the
**parameters**:

find_parameters(model) > $conditional > [1] "(Intercept)" "Speciesversicolor" "Speciesvirginica"

- Find the
**outcome’s name**:

find_response(model) > [1] "Sepal.Length"

- Find the
**formula**:

find_formula(model) > $conditional > Sepal.Length ~ Species

- Find the
**variables in the formula**:

find_variables(model) > $response > [1] "Sepal.Length" > > $conditional > [1] "Species"

- Find the
**algorithm**:

find_algorithm(model) > $algorithm > [1] "OLS"

Moreover, `insight`

also includes functions to deal with **Bayesian** (`get_priors()`

) and **mixed models** (`find_random()`

).

`insight`

works on a high number of models (see the **list here**), and **continue to grow thanks to your suggestions**! As *easystats* is a new project in active development, do not hesitate to contact us if **you want to get involved 🙂**

**Check out our other blog posts**!*here*

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