Descriptive Discriminant Analysis
Discriminant analysis comprises two approaches to analyzing group data: descriptive discriminant analysis (DDA) and predictive discriminant analysis (PDA). Both use continuous (or intervally scaled) data to analyze the characteristics of group membership. However, PDA uses this continuous data to predict group membership (i.e., How accurately can a classification rule classify the current sample into groups?), while DDA attempts to discover what continuous variables contribute to the separation of groups (i.e., Which of these variables contribute to group differences and by how much?). In addition to the primary goal of discriminating among groups, DDA can examine the most parsimonious way to discriminate between groups, investigate the amount of variance accounted for by the discriminant variables, and evaluate the relative contribution of each discriminant (continuous) variable in ...
Looks like you do not have access to this content.
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
- All
- A
- B
- C
- D
- E
- F
- G
- H
- I
- J
- K
- L
- M
- N
- O
- P
- Q
- R
- S
- T
- U
- V
- W
- X
- Y
- Z