Data Analysis for Psychology in R 3
2023/24

Course description

Data Analysis for Psychology in R 3 (DAPR3) is a course undertaken by 3rd year students in Psychology. It introduces statistical tools that are invaluable for analysing many types of psychological study, and prepares students for their dissertations. Following closely from DAPR2, the first block extends the linear model to analyses of "hierarchical data", in which observations are clustered in higher-level groups (e.g. trials within participants, or students within schools). DAPR3 provides students with a strong foundation in multilevel modelling, in which it is possible to capture variation in the outcome that is associated with characteristics at these different levels. The second block of DAPR3 introduces methods allowing us to analyse processes that are more complex than a simple "x predicts y". Following an introduction to path analysis and mediation ("x predicts z predicts y"), we move to studying data reduction techniques that allow us to summarise multiple correlated variables into either weighted composites or underlying latent factors.

Week Slides Workbook
Welcome Course Introduction
Week 1 Linear Model Refresher
Clustered Data
LAB: Regression Refresh | Clustered Data
Week 2 Introduction to Multilevel Models
Inference in Multilevel Models
LAB: Intro to Multilevel Models
Week 3 Assumptions and Diagnostics
Centering
LAB: Assumption & Diagnostics | Centering
Week 4 Random Effect Structures
Model Building
(Optional) Logistic Multilevel Models
LAB: Random Effect Structures | Logistic MLM

Week 5 Research Questions & Writing Up
LAB: Recap
LMM datasets
Week 6 --- ---
Week 7 Path Analysis LAB: Path Analysis
Week 8 Path Mediation LAB: Path Mediation
Week 9 Principal Component Analysis (PCA) LAB: PCA
Week 10 Exploratory Factor Analysis (EFA) I LAB: EFA I
Week 11 Exploratory Factor Analysis (EFA) II LAB: EFA II

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