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- Mod 1 - Foundation
- Mod 2 - Simple Reg
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Mod 3 - Multiple Reg
- 3.1 Overview
- 3.2 The Model
- 3.3 Assumptions
- 3.4 Modelling LSYPE Data
- 3.5 Model 1: Ordinal Explanatory Variables
- 3.6 Model 2: Dichotomous Explanatory Variables
- 3.7 Model 3: Nominal Variables
- 3.8 Predicting Scores
- 3.9 Model 4: Refining the Model
- 3.10 Comparing Coefficients
- 3.11 Model 5: Interaction Effects 1
- 3.12 Model 6: Interaction Effects 2
- 3.13 Model 7: Value Added Model
- 3.14 Diagnostics and Assumptions
- 3.15 Reporting Results
- Quiz
- Exercise
- Mod 4 - Log Reg
- Mod 5 - Ord Reg
- Further Adventures
- PDFs
- Videos
- Extensions
Using Statistical Regression Methods in Education Research
Module 3 - Multiple Linear Regression
You can jump to specific pages using the contents list below. If you are new to this module start at the overview and work through section by section using the 'Next' and 'Previous' buttons at the top and bottom of each page. Be sure to tackle the exercise and the quiz to get a firm understanding. This Module is also available as a downloadable PDF for those of you who prefer to read from a page. You do miss out on the glossary and some of the site's more interactive features though... Module 3: Multiple Linear Regression Contents
3.2 The Multiple Linear Regression Model 3.3 Assumptions of Multiple Linear Regression 3.4 Using SPSS to model the LSYPE data 3.5 A model with a ordinal explanatory variable (Model 1) 3.6 Adding dichotomous nominal explanatory variables (Model 2) 3.7 Adding nominal variables with more than two categories (Model 3) 3.8 Predicting scores using the regression model 3.9 Refining the model: treating ordinal variables as dummy variables (Model 4) 3.10 Comparing coefficients across models 3.11 Exploring interactions between a dummy and a continuous variable (Model 5) 3.12 Exploring interactions between two nominal variables (Model 6) 3.13 A value added model (Model 7) |
