restucture headings

docs/src/index.md

@@ -8,6 +8,8 @@ You can easily define custom objective functions and other parts of the model.
 At the same time, it is (very) fast.
 These properties enable SEM researchers (such as you!) to play around with ideas (extensibility) and run extensive simulations (speed) to evaluate these ideas and users to profit from the resulting innovation.
 
+## Get Started
+
 To get started, we recommend the following order:
 
 1. install the package ([Installation](@ref)),
@@ -16,6 +18,18 @@ To get started, we recommend the following order:
 
 After that, if you are interested in specifying a custom loss functions or other parts, you can proceed with [Extending the package](@ref).
 
+## Target Group
+
+You may consider using this package if you need **extensibility** and/or **speed**, e.g.
+- you want to extend SEM (e.g. add a new objective function)
+- you want to extend SEM, and your implementation needs to be fast
+- you want to fit the same model(s) to many datasets (bootstrapping, simulation studies)
+- you are planning a study and would like to do power simulations
+
+For examples of how to use the package, see the Tutorials.
+
+## Batteries Included
+
 Models you can fit out of the box include
 - Linear SEM that can be specified in RAM notation
 - ML, GLS and FIML estimation
@@ -30,15 +44,7 @@ You can choose to mix loss functions natively found in this package and those yo
 In such cases, you optimize over a sum of different objectives (e.g. ML + Ridge).
 This strategy also applies to gradients, where you may supply analytic gradients or opt for automatic differentiation or mixed analytical and automatic differentiation.
 
-You may consider using this package if you need **extensibility** and/or **speed**, e.g.
-- you want to extend SEM (e.g. add a new objective function)
-- you want to extend SEM, and your implementation needs to be fast
-- you want to fit the same model(s) to many datasets (bootstrapping, simulation studies)
-- you are planning a study and would like to do power simulations
-
-For examples of how to use the package, see the Tutorials.
-
-## Installation
+### Installation
 You must have [julia](https://julialang.org/downloads/) installed (and we strongly recommend using an IDE of your choice; we like VS Code with the Julia extension).
 
 To install the latest version of our package from GitHub, use the following commands: