Lecture Outline Part Two

Part Two: Advanced Techniques and Topics

I. Preliminaries

A. Discussion of First Exam
B. Details about Term Paper
C. Overview of Part Two

II. Categorical (Nominal, Qualitative) Measures

A. Dependent Variables

1. Multiple Regression
2. Discriminant Analysis
3. Logistic Regression

B. Independent Variables

1. Single Categorical Variable

a. Dichotomous: Dummy Variable Coding
b. Polytomous: Dummy, Effect, and Orthogonal Coding

2. Multiple Categorical Variables

a. Dummy Coding
b. Significance Tests: Orthogonal versus Nonorthogonal Categories

3. Categorical and Numerical Variables Combined

a. Definition and Interpretation
b. Significance Tests

III. Multiplicative Functions

A. Interaction Effects

1. Three Types

a. Nominal X Nominal (i.e., Qualitative X Qualitative or Categorical X Categorical)
b. Nominal X Numerical (i.e., Qualitative X Quantitative or Categorical X Continuous)
c. Numerical X Numerical (i.e., Quantitative X Quantitative or Continuous X Continuous)

2. Complications

a. Multicollinearity
b. Significance Tests
c. Interpretation: What does “control” mean with multiplicative terms in the equation?

B. Curvilinear Relations

1. Multiplicative Terms in a Single Numerical Variable

a. Quadratic Functions
b. Higher-Order Polynomial Functions

2. Precautions

a. Multicollinearity
b. Confounding Curvilinear and Interaction Effects
c. Alternatives to Polynomial Functions

C. Combined Models

1. Nonadditive Nonlinear Causal Effects
2. Precautions

IV. Complications

A. Outliers
B. Violated Assumptions
C. Missing Data

V. Review and Exam II

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