Multivariate Data Analysis Chapter 5 – Discrimination Analysis and Logistic Regression

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Multivariate Data Analysis Chapter 5 – Discrimination Analysis and Logistic Regression

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Multivariate Data Analysis Chapter 5 – Discrimination Analysis and Logistic Regression

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Multivariate Data AnalysisChapter 5 – Discrimination Analysis and Logistic Regression

MIS 6093 Statistical Method

Instructor: Dr. Ahmad Syamil

- What Are Discrimination Analysis and Logistic Regression?
- Analogy with Regression and MANOVA
- Hypothetical Example of Discriminant Analysis
- A Two Group Discriminant Analysis: Purchasers Versus Nonpurchasers
- A Geometric Representation of the Two Group Discriminant Function
- A Three-group Example of Discriminant Analysis: Switching Intentions

- Stage 1: Objectives of Discriminant Analysis
- Stage 2: Research Design for Discriminant
Analysis

- Selection of Dependent and Independent Variables
- Sample Size
- Division of the Sample

- Stage 3: Assumptions of Discriminant
Analysis

- Stage 4: Estimation of the Discriminant Model
and Assessing Overall Fit

- Computation Method
- Statistical Significance
- Assessing Overall Fit
- Calculating Discriminant Z Score
- Evaluating Group Differences
- Assessing Group Membership Prediction Accuracy

- Casewise Diagnostics
- Misclassification of Individual Cases

- Summary

- Stage 5: Interpretation of the Results
- Discriminant Weights
- Discriminant Loadings
- Partial F Values
- Interpretation of Two or More Functions
- Rotation of the Discriminant Functions
- Potency Index
- Graphical Display of Discriminant Loadings

- Which Interpretive Method to Use?

- Stage 6: Validation of the Results
- Split-Sample or Cross-Validation Procedures
- Profiling Group Differences

- Logistic Regression: Regression with a Binary Dependent Variable
- Representation of the Binary Dependent Variable
- Estimating the Logistic Regression Model
- Interpreting the Coefficients
- Assessing the Goodness-of-Fit of the Estimated Model
- Testing for Significance of the Coefficients

- Other Similarities To Multiple Regression

- Stage 1: Objectives of the Discriminant Analysis
- Stage 2: Research Design of the Discriminant
Analysis

- Selection of Dependent and Independent Variables
- Sample Size
- Division of the Sample

- Stage 3: Assumption of Discriminant Analysis

- Stage 4: Estimation of the Discriminant Function and
Assessing Overall Fit

- Estimation of the Discriminant Function
- Assessing Overall Fit
- Casewise Diagnostics

- Stage 5: Interpretation of the Discriminant
Function

- Stage 6: Validation of the Discriminant Results
- A Managerial Overview

- Stage 1: Objectives of the Discriminant Analysis
- Stage 2: Research Design of the Discriminant
Analysis

- Stage 3: Assumptions in Discriminant Analysis
- Stage 4: Estimation of the Discriminant Function
and Assessment

- Estimation of the Discriminant Functions
- Statistical Significance
- Assessing Overall Fit
- Casewise Diagnostics

- Stage 5: Interpretation of Three-group
Discriminant Analysis Results

- Rotation
- Assessing the Contribution of Predictor Variables

- Stage 6: Validation of the Discriminant
Results

- A Managerial Overview

- An Illustrative Example of Logistic Regression
- Summary
- Questions
- References
………end