General Linear Model
The general linear model (GLM) provides a general framework for a large set of models whose common goal is to explain or predict a quantitative dependent variable by a set of independent variables that can be categorical or quantitative. The GLM encompasses techniques such as Student's t test, simple and multiple linear regression, analysis of variance, and covariance analysis. The GLM is adequate only for fixed-effect models. In order to take into account random-effect models, the GLM needs to be extended and becomes the mixed-effect model.
Vectors are denoted with boldface lower-case letters (e.g., y), and matrices are denoted with boldface upper-case letters (e.g., X). The transpose of a matrix is denoted by the superscriptT, and the inverse of a matrix is denoted by the superscript–1. ...
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Reader's Guide
Descriptive Statistics
Distributions
Graphical Displays of Data
Hypothesis Testing
Important Publications
Inferential Statistics
Item Response Theory
Mathematical Concepts
Measurement Concepts
Organizations
Publishing
Qualitative Research
Reliability of Scores
Research Design Concepts
Research Designs
Research Ethics
Research Process
Research Validity Issues
Sampling
Scaling
Software Applications
Statistical Assumptions
Statistical Concepts
Statistical Procedures
Statistical Tests
Theories, Laws, and Principles
Types of Variables
Validity of Scores
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Research Methods
