Unlocking the World of SEM, CFA, and Path Modeling

Welcome to my bimonthly blog dedicated to delving into the intricacies of structural equation modeling (SEM), confirmatory factor analysis (CFA), and path modeling. Within these pages, you'll find posts covering crucial aspects of SEM and CFA, applicable across various modeling platforms. Additionally, I'll provide guidance on implementing models using specific software, with a special focus on R/lavaan.

I'm Arndt Regorz and I am a statistics consultant specializing in offering support to students undertaking doctoral dissertations or master's theses. The main focus of my consultant's work is SEM/CFA and multilevel modeling. My academic background includes degrees in psychology (BSc. and MSc.) and business administration. I extend my services globally with clients in Europe, America, Asia, and Australia. Whether you're based on a different continent or nearby, you can book a video consultation with me in English or in German.

Most Recent Post

Multivariate Normality in a Lavaan Model (SEM, CFA, Path Analysis)
How to check the normality assumption

Earlier Posts

How to Calculate the A-priori Power For a Path Model Using semPower
How to perform an a-priori or a post-hoc power analysis for a path model

Comparing Paths in a Path Model With R/Lavaan
How to test whether two effects are significantly different from each other

SEM/CFA: AMOS or lavaan?
Why the z-test can lead to problematic conclusions in models with latent variables (CFA, SEM)

SEM/CFA: Be Careful With the Z Test
Why the z-test can lead to problematic conclusions in models with latent variables (CFA, SEM)

SEM/CFA: Checking the Linearity Assumption in R/lavaan
How to check the linearity assumption using factor scores for a CFA or an SEM in lavaan

What Modification Indices Don't Tell You
Which types of model improvement can't be directly seen from modification indices

Empirical Underidentification in SEM and CFA
Sources for empirical underidentification and how to prevent it from happening