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Spit Camp II – MLM Agenda

DAY 1

Welcome, Background, Data, and R

  • Welcome
  • Things you should know before analysis
  • What’s correlated data?
  • Modeling techniques for correlated data: traditional vs advanced
  • What’s Multi-Level Modeling (MLM)?
  • MLM assumptions
  • Your research question in hypothesis testing framework
  • Data preparation for longitudinal data analysis
  • Introduction to example cortisol data
  • A brief R tutorial

DAY 2

Random Intercept/Slope Models (Exploratory Data Analysis, Model Fitting, and Diagnostics in R) Interpretations of Results

  • Introduction to MLM for correlated data
  • Random intercept model
  • Random intercept/slope model
  • Exploration of different covariance structures for the repeated measure
  • Variations of random intercept/slope models
  • Cortisol toy data example

DAY 3

Additional Modeling Techniques, Individualized Data Analysis, Trouble Shooting, and Presenting Outputs

  • A brief review of additional modeling techniques such as non-linear and spline mixed effect modeling
  • Example MLM research papers
  • Getting to know your data
  • Assistance with individualized model fitting
  • Trouble shooting errors
  • Assistance with interpretation and presenting outputs
Pre-Register

UCI School of Social Ecology
Social Ecology I
Irvine, CA 92697-7050
www.uci.edu
www.socialecology.uci.edu

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