·
Workshop Objectives
·
Content Covered in Workshop
·
Resources to Continue Learning After Workshop
·
Introduction to Longitudinal Data Analysis (LDA)
o Alternatives and
Challenges
o Problems with Change
Scores
o Modeling as a Research
Paradigm
·
Latent Growth Curve Modeling (LGM)
o Thinking about and
modeling time
·
Orientation to General Latent Variable Modeling Framework
o Path Diagram Notation
o Covariance Structure
Modeling Perspectives on Latent Variables
·
Orientation to Mplus Modeling
o How to write an Mplus
command file
·
Example Data Set Overview
·
Getting Data into Mplus (Using SAS, SPSS, Stata, R; PC and MAC)
·
Workflow and Reproducibility
·
Confirmatory Factor Analysis (CFA)
·
Growth Curve Modeling
o Compare with SAS/PROC
Mixed

·
LGM Model Specification
·
LGM with covariates
o Time Invariant Covariates
o Time Varying Covariates
·
Using Mplus for LGM
·
Mplus Command Syntax
·
Missing Data Handling
·
Model Fit Assessment
·
Data Handling: Centering Covariates
·
NonLinear Development
·
Growth Mixture Modeling (GMM)
o Latent Class Analysis
(LCA) for Growth
o Assessing Fit
o Determining the number of
classes
o Exploratory and
Confirmatory LCA
o GMM with Covariates
o Importance of Theory and
Hypotheses for Driving Data Analysis
·
Multilevel Model Approach to Growth Curve Modeling with Mplus
·
Multiple Indicator Growth Curve Model
·
Modeling Retest Effects and Other Methods Artifacts
·
Resources to Continue Learning After Workshop

·
Knownclass Mixture Model
·
LGM in Randomized Controlled Trials
o Acceleration/Deceleration
o Punctuation
·
LGM using Bayesian Data Analysis
·
Latent Change Score Models
o Dual Change Score Model
·
Survival Analysis
o Continuous Time Survival
o Discrete Time Survival
·
Complex Models
o Strategies for Building
Complex Models
o Accelerated Longitudinal
Designs
o Multilevel LGM
o Parallel Process LGM
o Multiple Indicator LGM
with Measurement NonInvariance
o Joint Survival and Growth
Models
o Using Complex Sampling Weights
·
Responsible Conduct of Research
o Confidentiality
o Secondary Data Analysis
·
Resources to Continue Learning
After Workshop
