Brief Outline

Computer Setup

  • Installing software (R, RStudio, and packages)
  • Workspace orientation
  • Notebook workflow
  • Periodic updating

Data Management

  • Importing data files (SPSS, Excel, CSV, ect.)
  • Sub-setting (observations and variables)
  • Creating new variables
  • Saving revised data

Exploratory Data Analysis

  • Computing and tabulating summary statistics (M/SD, count/%)
  • Creating descriptive visualizations of distributions (boxplots, histograms) and relationships (scatter plots)

Testing Mean Differences

  • t-tests (independent groups, paired observations)
  • ANOVA (independent or between subjects, 1-way, 2-way)
  • RM ANOVA (repeated meausres, between subjects)
  • Mixed ANOVA (both independent and between subjects)
  • Visualizations (marginal means to prob interactions)
  • Post hoc tests (multiple corrections, contrast statements)

Regression

  • Calculating and visualizating correlation
  • Multiple regression models (fitting, tabulating results, graphicaly probing interactions)
  • Generalizing the distribution (GLM: logistic regression, poisson regression, ect.)
  • Moderation and Mediation
  • Average Marginal Effects

Mixed Effects Regression

  • Modeling clustered/hierarchical or longitudinal/repeated observations with multilevel models (MLM, LMM, GLMM, HLM), including:
  • Computing ICCs
  • Model fitting
  • Tabulating results
  • Visualizings (marginal means to prob interactions)
  • Generalized Estimating Equations (GEE)

Structural Equation Modeling

  • Latent variables
  • Path Analysis

Additional Topics

  • Room for Future Expansion

Copyright © 2018 Sarah Schwartz & Tyson Barrett. All rights reserved.