[Q] what are good, reliable SEM resources for beginners

[u/babydonuttravel]

I'm a PhD student looking to use SEM in my project, but I'm a complete beginner. I tried going to statistics professors for guidance but already two told me to use Claude.

I would really like to understand it and be able to do it myself. I'm going to be using R. I've been using online resources but sometimes I get different information (a basic example is some websites tell me to report the Cronbach alpha, others say that's not a good test for using with SEM).

What are some good resources or books I can use as a complete beginner for SEM?

[u/cluttered_custard]

kline's principles and practice of SEM is the standard starting point for most people i know. it's not super math heavy and walks through the logic before you ever touch software

if you want something more applied with R code, look for books or tutorials that use the lavaan package specifically. that's where most of the beginner friendly R material lives

the cronbach alpha thing is a good instinct to question. SEM folks tend to prefer composite reliability and other measures that account for measurement error, which alpha doesn't really do well. that's the kind of thing a good book will clear up early

[u/schotastic → u/cluttered_custard]

The software advice is good and generalizes beyond lavaan. Whatever software OP intends to use, there's bound to be SEM books written for it that are usually beginner-friendly

[u/Laerphon]

How're your fundamentals in math and statistics? If reasonably solid, the canonical SEM text is still Bollen (1989) Structural Equations with Latent Variables. I've also heard Kline's (2023) Principles and Practice of Structural Equation Modeling is accessible but haven't used it myself.

[u/schotastic → u/Laerphon]

I'm currently reading Bollen's 2026 update to this book. It's fantastic. Technical but not inaccessible.

[u/Laerphon → u/schotastic]

Oh wow, thanks for this, I hadn't realized he'd cranked out a new one. I'll have to pick it up.

[u/drehmomentwandler]

Check out Dan Curran and Patrick Bauer at Centerstat. Their SEM course is free and really good

[u/STATASUCKSBRO]

Cronbach alpha is not a test of whether SEM is appropriate. If a website says that, stop using it. Start with Kline and work the lavaan tutorials alongside it.

[u/GripIQ]

I have taught SEM for over 15 years - do you have basic math skills like matrix algebra and basic stats skills like a good understanding of GLM? If so I would look into learning tracing rules and then connecting that to the matrix algebra to understand why tracing rules work. Once you get down tracing rules and understand almost any model can be parameterized as a SEM/path model it becomes like a Rosetta Stone. For textbooks I would use Phil Wood’s text https://www.routledge.com/Understanding-Structural-Equation-Models-Models-of-Relationships-Between-Variables/Wood/p/book/9781032962429 - I took Phil’s classes through GLM and SEM and Advanced SEM and that understanding has let me publish tons of SEM related papers, find and report bugs in major SEM software, and so on. I also have a ton of slides that explain technical things in an approachable way that I could send you for free if you hit me up. I use Claude sometimes but I’d be careful - I have corrected it so much it calls me the “stats one” when we chat lol

[u/Much_Acadia6083]

To learn the fundamentals I’d suggest Loehlin & Beaujean Latent Variable Models.

[u/QuantMalcolm]

Kline's book on principles and practice of SEM is the standard starting point, way better than random blog posts. Lavaan package docs also have solid worked examples if you're in R.

[u/GhostGlacier]

https://www.jmp.com/en/statistics-knowledge-portal/structural-equation-modeling

Some intro material for building intuition.

[u/seanv507]

Have you used claude? I don't think the profs are suggesting vibe coding. They are telling you to have a dialogue with claude to learn the technique. ie "Why should I use SEM in my analysis", "Should I report Cronbach alpha" etc

[u/babydonuttravel → u/seanv507]

I get that, but if the information is already compiled in a book I would personally prefer that. I can go to claude after ive done reading with questions i have on that. Also, technically we're not allowed to share our research questions or actual variables or data with Claude because privacy isnt guaranteed, and that cant be leaked until the paper is published, so I would have to keep my questions general anway.