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The Center for Statistical Training

by Curran-Bauer Analytics

Statistical training in advanced quantitative methods for researchers in the social, health, and behavioral sciences.

Online Workshops

Accessible, effective, comprehensive training in statistics, data science, and research methods are just one click away.

Learn More
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Free 3-Day SEM Workshop

Upcoming Livestream Workshops

Registration for our Winter Institute livestreams is now available!  Check out the four short courses we're offering live this December and January.

Can't fit the livestream into your schedule or need a different workshop? No problem. All of our previously offered workshops are available for self-paced access. You get replays and materials for a full year. Try it out with our FREE workshop, Introduction to Structural Equation Modeling!

Modern Missing Data Analysis

December 6-8, 2023
Livestream & Replay Access
Instructor: Craig Enders

Multilevel Models for Hierarchical Data

December 11-13, 2023
Livestream & Replay Access
Instructors: Dan Bauer & Patrick Curran

Latent Curve Models

December 14-16, 2023
Livestream & Replay Access
Instructor: Dan Bauer & Patrick Curran

Mixture Modeling and Latent Class Analysis: A Short Course

January 3-5, 2024
Livestream & Replay Access
Instructor: Dan Bauer

Self-Paced Access to Prior Workshops

Set your own schedule by registering for self-paced access to recently conducted workshops. You will receive access to all workshop videos for 1 year from purchase and all workshop materials other than the videos are yours to keep (detailed lecture notes and, when applicable, software demonstration notes, data files and syntax).

Free Introduction to Structural Equation Modeling

Replay Access: 1 year
Length: Three Days
Instructors: Dan Bauer & Patrick Curran

Mixture Modeling and Latent Class Analysis

Replay Access: 1 year
Length: Five Days
Instructors: Dan Bauer & Doug Steinley

Applied Measurement Modeling

Replay Access: 1 year
Length: Four Days
Instructors: Patrick Curran & Greg Hancock

Causal Inference

Replay Access: 1 year
Length: Five Days
Instructor: Doug Steinley

Multilevel Modeling

Replay Access: 1 year
Length: Five Days
Instructors: Dan Bauer & Patrick Curran

Applied Qualitative Research

Replay Access: 1 year
Length: Five Days
Instructors: Greg Guest & Emily Namey

Modern Missing Data Analysis

Replay Access: 1 year
Length: Three Days
Instructor: Craig Enders

Machine Learning: Theory and Applications

Replay Access: 1 year
Length: Five Days
Instructor: Doug Steinley

Sample Size Planning for Power and Accuracy

Replay Access: 1 year
Length: Three Days
Instructor: Samantha Anderson

Network Analysis

Replay Access: 1 year
Length: Five Days
Instructor: Doug Steinley

Applied Research Design Using Mixed Methods

Replay Access: 1 year
Length: Two Days
Instructor: Greg Guest

Introduction to Data Visualization in R

Replay Access: 1 year
Length: Four Days
Instructor: Michael Hallquist

Longitudinal Structural Equation Modeling

Replay Access: 1 year
Length: Five Days
Instructors: Dan Bauer & Patrick Curran

Introduction to Quantitative Meta-Analysis

Replay Access: 1 year
Length: Four Days
Instructor: Tasha Beretvas

Analyzing Intensive Longitudinal Data

Replay Access: 1 year
Length: Five Days
Instructors: JP Laurenceau & Niall Bolger

News & Updates

What are ROC curves and how are these used to aid decision making?

September 18, 2023
One of the most vexing challenges in all of statistics is the need to make a valid and reliable probabilistic assessment about some unknown condition or state of affairs based solely on information gathered from sample data. Indeed, this is the foundation of traditional null hypothesis testing: there is some unknown condition in the population (the null hypothesis is either...
Keep Reading about What are ROC curves and how are these used to aid decision making?

This Week on CenterStat Unscripted: Exploratory & Confirmatory Factor Analysis

February 28, 2023
This Thursday at noon (3/2, 12:00 pm ET), Dan and Patrick introduce the basics of factor analysis, both exploratory and confirmatory, and describe potential advantages and disadvantages to each. They begin by discussing traditional factor analytic methods and then explore more recent developments in measurement and scoring. The conclude with how these methods might be best used in practice and...
Keep Reading about This Week on CenterStat Unscripted: Exploratory & Confirmatory Factor Analysis

This Week on CenterStat Unscripted: An Introduction to the Latent Curve Model

February 22, 2023
This Thursday at noon (2/23, 12:00 pm ET), Dan and Patrick will bicker their way through an introduction to the latent curve model (LCM), a type of structural equation model commonly used to analyze change over time. They begin by discussing two time-point longitudinal models, and then extend this to three or more time points. They describe the theoretical concept...
Keep Reading about This Week on CenterStat Unscripted: An Introduction to the Latent Curve Model

Announcing CenterStat Unscripted: A New Weekly YouTube Livestream on Quantitative Methods

February 2, 2023
In large part because Dan and Patrick have jobs from which they can't be fired, they keep coming up with random activities with which to entertain themselves (and possibly others). CenterStat is thus excited to announce their latest boondoggle: CenterStat Unscripted, a weekly YouTube Live broadcast in which Dan and Patrick ad lib their way through a different topic in...
Keep Reading about Announcing CenterStat Unscripted: A New Weekly YouTube Livestream on Quantitative Methods

What exactly qualifies as intensive longitudinal data and why am I not able to use more traditional growth models to study stability and change over time?

October 14, 2022
Recent years have seen increasing interest in the collection and analysis of intensive longitudinal data (or ILD) to generate unique insights into within-person processes and change over time. In this post, we first define ILD by contrasting it to data obtained from other common longitudinal designs. Next, we consider the distinct features of ILD that we must address and can...
Keep Reading about What exactly qualifies as intensive longitudinal data and why am I not able to use more traditional growth models to study stability and change over time?

CenterStat Partners with APA to Offer Free Training on Intensive Longitudinal Data

August 28, 2022
With the evolution and ever greater penetration of smartphones, other personal electronic devices, and wearable technologies, scientists are increasingly able to collect and analyze Intensive Longitudinal Data (ILD). The extensive sampling of observations for each person in ILD provides researchers with unique opportunities to study psychological processes as they unfold in real time. To help participants learn more about how to conduct...
Keep Reading about CenterStat Partners with APA to Offer Free Training on Intensive Longitudinal Data

What’s the best way to determine the number of latent classes in a finite mixture analysis?

November 11, 2021
Finite mixture models, which include latent class analysis, latent profile analysis, and growth mixture models, have grown greatly in popularity over the past decade or so.  Most statistical models assume a unitary (or homogeneous) population wherein all observations are governed by the same basic process.  In contrast, finite mixture models aim to identify latent subgroups within the population, sometimes referred...
Keep Reading about What’s the best way to determine the number of latent classes in a finite mixture analysis?

My advisor told me to use principal components analysis to examine the structure of my items and compute scale scores, but I was taught not to use it because it is not a “true” factor analysis. Help!

October 12, 2021
Help, indeed. This issue has been a source of both confusion and contention for more than 75 years, and papers have been published on this topic as recently as just a few years ago. A thorough discussion of principal components analysis (PCA) and the closely related methods of exploratory factor analysis (EFA) would require pages of text and dozens of...
Keep Reading about My advisor told me to use principal components analysis to examine the structure of my items and compute scale scores, but I was taught not to use it because it is not a “true” factor analysis. Help!

Second Annual Winter Institute

September 21, 2021
This December and January we will again be conducting livestream classes on our most popular topics, including a new 3-day workshop on Causal Inference. All classes come with six months access to video recordings to catch up later when life interferes (because it usually does). We hope you'll consider joining us.  And don't forget that you can also obtain asynchronous access to any of our great workshops...
Keep Reading about Second Annual Winter Institute

I fit a multilevel model and got the warning message “G Matrix is Non-Positive Definite.” What does this mean and what should I do about it?

July 22, 2021
Anyone who uses multilevel models will eventually encounter the dreaded “G matrix is non-positive definite” message (or “Tau Matrix” or “Psi Matrix”, depending on the labeling used by your software). This anxiety-inducing warning is often a signal that something is wrong in your model that needs fixing. With an NPD G matrix, the obtained estimates usually reflect an “improper” solution...
Keep Reading about I fit a multilevel model and got the warning message “G Matrix is Non-Positive Definite.” What does this mean and what should I do about it?

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