## How can I estimate statistical power for a structural equation model?

This is a question that often arises when using structural equation models in practice, sometimes once a study is completed but more often in the…

## What are modification indices and should I use them when fitting SEMs to my own data?

This is a great question and is one that prompts much disagreement among quantitative methodologists. Nearly all confirmatory factor analysis or structural equation models impose…

## Do you have any materials that demonstrate how to estimate structural equation models using lavaan in R?

This is a question we often hear, particularly from students and junior researchers who don’t have access to expensive commercial software for fitting structural equation…

## How do you choose the best longitudinal data analytic method for testing your research questions?

We have worked with statistical models for longitudinal data for more than two decades and this remains a vexing question to us both. There are…

## What is the difference between a growth model estimated as a multilevel model versus as a structural equation model?

This very common question reflects a great deal of unnecessary confusion about how to select a specific analytic approach for modeling longitudinal data. The general…

## How can I define nonlinear trajectories in a growth curve model?

Growth curve models, whether estimated as a multilevel model (MLM) or a structural equation model (SEM), have become widely used in many areas of behavioral,…

## Can I estimate an SEM if the sample data are not normally distributed?

Continuous distributions are typically described by their mean (central tendency), variance (spread), skew (asymmetry), and kurtosis (thickness of tails). A normal distribution assumes a skew…

## How do I know if my structural equation model fits the data well?

This is one of the most common questions we receive and, unfortunately, there are no quick answers. However, there are some initial guidelines that can…

## Best Methods for Handling Missing Data in Intensive Longitudinal Designs

In nearly every discipline within the behavioral, health, and educational sciences, longitudinal data have become requisite for establishing temporal precedence and distinguishing inter-individual differences in…

## Syntax for Computing Random Effect Estimates in SPSS

Many programs can be used to fit multilevel models. For instance, in our multilevel modeling summer workshop, we demonstrate three programs: SAS, SPSS, and Stata.…