Importantly, the book offers a plethora of nuggets of knowledge that are near-impossible to find out there (at least it’s impossible to find them without scouring the internet and various obscure fora), like how set up loop plots or how to flexibly use the “model constraint” command for your own analyses.

A whole set of different mediation models. Whatever your research topic, you are bound to want to answer the “why” and “how” questions, which will call for the introduction of causal chains and mediators. But mediation models can vary greatly and having this book handy will really  make a difference.

Trouble-shooting problems in a detailed way. For example, what can you do if you get a standardized coefficient greater than 1?

Detailed examples of a multitude of regression models, with explanations of how to interpret the output files. If you’re a beginner and need to do a zero-regression Poisson regression because your outcome variable is a count variable (e.g., nr. of crimes or nr. of hours spend playing video games), you can find how to specify a simple model in the user guide. But interpreting the output is a whole different ball-game and this book really provides all the hand-holding you might need.

Easy explanation of the Maths behind regression models (I’ve put this first because it’s such a relief to find all this infomation in one place, instead of struggling to learn it from fragmented sources – but if this is not your cup of tea, move on to the next point).