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, health, and education sciences. The most common type of growth model defines a linear trajectory in which the time scores defining the slopes increment evenly for equally spaced repeated measures (e.g., values representing time are...
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 and kurtosis of zero, but truly normal distributions are rare in practice. Unfortunately, the fitting of standard SEMs to non-normal data can result in inflated model test statistics (leading models to be rejected more often...
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 be followed when assessing the fit of an SEM. For most SEMs, the goal of the analysis is to define a model that results in predicted values of the summary statistics (sometimes called “moment structures”...
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 intra-individual change. Whereas traditional longitudinal designs often obtained repeated assessments at monthly or even yearly intervals, recent advances in mobile technology have allowed for the collection of multiple assessments throughout a single day. These so-called...
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. Unlike SAS, Stata, and many other programs, however, SPSS does not currently offer the option to output estimates of the random effects. Obtaining estimates of the random effects can be useful for a variety of...
Using Listservs to get Advice
Although a bit old school, listservs such as SEMNET (for latent variable models) and the Multilevel Discussion List remain useful resources when grappling with quantitative modeling issues. You can search the archives to see if your question has come up before or post a new question to obtain fresh feedback / opinions from list members. Quick tip: use the “receive...
In their blog, Dan and Patrick respond to commonly asked questions about a variety of topics behavioral, educational, and health research including experimental design, measurement, data analysis, and interpretation of findings. The responses are intentionally brief and concise (sort of), and additional resources are provided such as recommended readings, provision of exemplar data and computer code, or links to other potential learning materials. Readers are welcome to submit questions for future responses.