Use CenterStat Curricular Pathways to Guide your Knowledge and Skills Development
CenterStat offers workshops on a variety of topics that can be taken in any order. For those seeking to develop broad expertise within one or more key areas of research methods and statistics, these classes can also be combined into four curricular pathways:
Foundations Pathway
Broaden your knowledge with these foundational classes:
- Introduction to Sample Size Planning for Statistical Power: Optimize the effectiveness and efficiency of your research
- Foundations of Bayesian Estimation and Inference: Learn how to conceptualize, specify, estimate and interpret commonly used models within the Bayesian framework
- Modern Missing Data Analysis: Learn how to handle missing data due to non-response, attrition, or by design
- Introduction to Structural Equation Modeling: Extend from path analysis and confirmatory factor analysis to SEMs with latent variables
- Multilevel Models for Hierarchical Data: Analyze hierarchically nested data (e.g., students within schools)
- Applied Qualitative Research: Address how and why questions by implementing qualitative research designs and methods
Measurement / Latent Variable Modeling Pathway
Improve your ability to conceptualize and measure latent constructs with these classes:
- Applied Measurement Modeling: Use exploratory and/or confirmatory factor analysis to develop valid measures your constructs
- Introduction to Structural Equation Modeling: Extend from path analysis and confirmatory factor analysis to SEMs with latent variables
- Longitudinal Structural Equation Modeling: Determine whether construct measurement shifts over time by testing longitudinal factorial invariance and use latent factors to model change over time
- Mixture Modeling & Latent Class Analysis: Learn about discrete latent variable models, such as latent class/profile analysis
- Network Analysis: Conduct network psychometrics, an emerging alternative to factor analytic approaches to measurement
Longitudinal Data Analysis Pathway
Grow your expertise in longitudinal data analysis with these classes:
- Multilevel Models for Longitudinal Data: Learn how to fit a variety of growth curve models within a multilevel modeling framework
- Analyzing Intensive Longitudinal Data: Examine within-person and within-dyad processes in intensive longitudinal data
- Latent Curve Modeling: Get extensive coverage of latent curve models for the analysis of stability and change over time
- Longitudinal Structural Equation Modeling: Includes coverage of latent curve models as well as other longitudinal structural equation models
- Modern Missing Data Analysis: Understand how attrition can affect your results, and how to account for it using state-of-the-art methods
Data Science Pathway
Learn how to visualize and mine data with these classes:
- Network Analysis: Analyze the connections between your observations, whether individuals in a social network, regions of interest in fMRI data, or items in a psychometric network
- Machine Learning for Classification Problems: Learn about traditional and state-of-the-art approaches to statistical learning (artificial intelligence) for predicting classifications
- Machine Learning: Theory and Applications: Includes coverage of statistical learning techniques for prediction of both classifications and continuous criterion variables
- Mixture Modeling & Latent Class Analysis: Apply unsupervised learning techniques to identify unobserved subgroups and reveal structure in your data
Applied Qualitative Research Pathway
Learn how to conduct qualitative research with these classes:
- Foundations: Free class that provides an overview of epistemological perspectives associated with qualitative research and situates the other workshops within this pathway.
- In-Depth Interviews: Covers in-depth interviewing from an applied perspective, including best practices, developing a guide, and use of inductive probing.
- Focus Groups: Covers focus groups from an applied perspective, including best practices, developing a guide, qualitative data management, using a transcription protocol, and digital platforms.
- Thematic Analysis: Covers the analysis of text data obtained from qualitative research methods, such as focus groups or in-depth interviews.
Get all four at a 20% discount with our Applied Qualitative Research Bundle
