Lecture 13: Coding Schemes for Regression
Reading Assignment:
Muller and Fetterman, Chapter 12: Coding Schemes for Regression (Required)
Goals for the Next Two Weeks
1. Understand various coding sche
Lecture 12: Selecting the Best Model
Reading Assignment:
Muller and Fetterman, Chapter 11: Selecting the Best Model (Required)
Selecting the best model, while perhaps one of the most common data anal
Lecture 11: Transformations
Reading Assignment:
Muller and Fetterman, Chapter 10: Transformations (Required)
Transformation of the response and/or predictor variables may correct violations of
homoge
Lecture 7: Correlations
Reading Assignment:
Muller and Fetterman, Chapter 6: Correlations (Required)
For two random variables X and Y , recall that the correlation is dened as
= Corr(X, Y ) =
where
Lecture 5: Multiple Regression: General Considerations
Reading Assignment:
Muller and Fetterman, Chapter 4: Multiple Regression (Required)
Why use more than one covariate in a model?
Why not t separ
Lecture 6: Testing Hypotheses in Multiple Regression
Reading Assignment:
Muller and Fetterman, Chapter 5: Testing Hypotheses in Multiple Regression
(Required)
After tting a model, one seeks to draw i
Lecture 3: General Linear Model: Estimation and Testing
Reading Assignment:
Muller and Fetterman Chapter 2: Statement of the Model, Estimation, and Testing
(Required)
We will consider the case in whi
Lecture 19: Power & Sample Size Calculation
Reading Assignment:
Muller and Fetterman, Chapter 17: Understanding and Computing Power for the
GLM (Required)
UNC Biostatistics 663, Spring 2015
1
Motivat
Lecture 1: Introduction and Overview
Reading
Muller and Fetterman Chapter 1: Examples and Limits of the GLM
Linear models are used to study how a quantitative response variable depends on one or
more
Lecture 16: ANCOVA and the Full Model
Reading Assignment:
Muller and Fetterman, Chapter 16: The Full Model in Every Cell (ANCOVA as a
Special Case) (Required)
Understanding this chapter allows you to
Lecture 17: Logistic Regression
Often, the response of interest in a scientic study is a binary variable, such as
DISEASED/NOT DISEASED or DEAD/ALIVE. In this case, what are the problems with
the line
Lecture 14: One-Way ANOVA
Reading Assignment:
Muller and Fetterman, Chapter 13: One-Way ANOVA (Required)
We use analysis of variance (ANOVA) to answer questions like the following.
Do two or more gr
Lecture 18a: Mixed effect model
Reading Assignment:
Muller and Fetterman, Chapter 15: Special Cases of Two-Way ANOVA and Random
Effects (Required)
Mixed effects = xed effects + random effects. Mixed
Lecture 15: Two-Way ANOVA
Reading Assignment:
Muller and Fetterman, Chapter 14: Complete, Two-Way Factorial ANOVA
(Required)
In two-way analysis of variance (ANOVA), we wish to evaluate the importanc
Lecture 8: GLM Assumption Diagnostics
Reading Assignment:
Muller and Fetterman, Chapter 7: GLM Assumption Diagnostics (Required)
Wait, what are those assumptions agagin?
Homogeneity, Independence, Li