Data Analysis for Psychology in R 3
2022/23

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.

Course materials 2022/23

Week Lecture Workbook
1 Welcome and Course Intro
Linear Models and Clustered Data
Regression Refresh | Clustered Data
2 Introducing Multilevel Models LM to MLM
3 Assumptions & Diagnostics for Multilevel Models Assumptions & Diagnostics
4 Centering Predictors, and Generalized Multilevel Models Centering | Logistic
5 Multilevel Models: Research Questions & Writing up Recap
6 Break Week!
7 Introducing Path Analysis Path Analysis
8 Path Mediation Path Mediation
9 Principal Component Analysis (PCA) Dimension Reduction
10 Exploratory Factor Analysis I EFA: Part 1
11 Exploratory Factor Analysis II EFA: Part 2

Extra Documents

Example Analysis: Rpt & Mixed ANOVA
Example Analysis: MLM Repeated Measures
Example Analysis: MLM Intervention
Example Analysis: MLM Many Trials
Explainer: 3-level model equation
Explainer: PCA & Unequal Variances
Example Analysis: EFA

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