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

Lavaan (CFA, SEM): Are Your Models Nested?
How to automatically check for model nesting

Earlier Posts

CFA: Cross Loadings
A possible source for model misspecification

Lavaan: Small N Chi Square Tests
How to get a correct model test in a lavaan model (SEM, CFA, path analysis) with a small sample size

Interpreting Covariances/Correlations in Path Analysis
Covariances between exogenous variables have a different meaning than between endogenous variables

Cluster Robust Standard Errors in R/Lavaan
How to deal with nested data in a lavaan model

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

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?
Which is the better program for your needs?

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