Final Exam, December 2001
Categorical Data Analysis for Epidemiologic Studies, CHL5407H
INSTRUCTIONS
You have until 3 p.m. to complete this exam.
Show all of your work so that partial credit can be given.
Clearly state any assumptions you make in answe
Final Exam, April 2003
Categorical Data Analysis for Epidemiologic Studies, CHL5407H
INSTRUCTIONS
You have until 3 p.m. to complete this exam.
Show all of your work so that partial credit can be given.
Clearly state any assumptions you make in answerin
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ST3241 Categorical Data Analysis I
An Introduction
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Some Objectives Of This Course
Analyzing binomial and Poisson variables in real data.
Visualizing and analyzing categorical data.
How to use SAS and / or R for the above purposes.
Provid
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ST3241 Categorical Data Analysis I
Three-way Contingency Tables
An Introduction: Conditional Associations
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Example: Death Penalty Data
Death Penalty
Victims
Defendants
Race
Race
Yes
No
White
White
53
414
Black
11
37
White
0
16
Black
4
139
Bla
Midterm Exam
Categorical Data Analysis, CHL5407H
INSTRUCTIONS
You have until 3:00 p.m. to complete this exam.
Show all of your work so that partial credit can be given.
Clearly state any assumptions you make in answering a question.
This is an open bo
Lecture Notes
on
Actuarial Mathematics
Jerry Alan Veeh
May 9, 2003
Copyright 2003 Jerry Alan Veeh. All rights reserved.
0. Introduction
The objective of these notes is to present the basic aspects of the theory of
insurance, concentrating on the part of t
Outline
7.1: Model for Nominal Response;
Chapter 7. Logit Models for Multivariate
Responses
7.2: Model for Ordinal Response;
7.3: other link functions;
Deyuan Li
7.4: alternative ordinal-response models;
School of Management, Fudan University
7.5: te
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ST3241 Categorical Data Analysis I
Generalized Linear Models
Some More Discussions
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Deviance
A saturated model has a separate parameter for each
observation giving a perfect t.
Let denote the estimate of for the saturated model,
correspondi
Outline
8.1: Loglinear Model for Two-way contingency Tables;
Chapter 8. Loglinear Models for Contingency
Tables
8.2: Loglinear Model for Independence and Interaction in
Three-way Contingency Tables;
Deyuan Li
8.3: Inference for Loglinear Models;
School
Outline
10.1: Comparing Dependent Proportions;
Chapter 10. Models for Matched Pairs
10.2: Conditional Logistic Regression for Binary Matched
Paries;
Deyuan Li
10.3: Marginal Models for Squared Contingency Tables;
School of Management, Fudan University
Outline
Chapter 6. Building and Applying Logistic
Regression Models
6.1 Strategies in Model Selection
6.2 Logistic Regression Diagnostics
Deyuan Li
6.3 Inference about Conditional Association in 2 K Tables
School of Management, Fudan University
Feb. 28
Outline
5.1 Interpreting Parameters in Logistic Regression
Chapter 5. Logistic Regression
5.2 Inference for Logistic Regression
Deyuan Li
5.3 Logit Models with Categorical Predictors
School of Management, Fudan University
5.4 Multiple Logistic Regress
Outline
4.1 Generalized Linear Models
Chapter 4. Introduction to Generalized Linear
Models
4.2 Generalized Linear Models for Binary Data
4.3 Generalized Linear Models for Counts
Deyuan Li
4.4 Moments and Likelihood for Generalized Linear Models
School
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ST3241 Categorical Data Analysis I
Logistic Regression
An Introduction and Some Examples
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Example Applications
Business Applications
The probability that a subject pays a bill on time may use predictors
such as the size of the bill, annual
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ST3241 Categorical Data Analysis I
Loglinear Models
2 2 Models For Contingency Tables
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Two-way Tables
Consider an I J contingency table that crossclassies a
sample of n subjects on two categorical responses.
Let Yij be the observed cell fre
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ST3241 Categorical Data Analysis I
Multicategory Logit Models
Logit Models For Nominal Responses
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Models For Nominal Responses
Y is nominal with J categories.
Let cfw_1 , , J denote the response probabilities with
1 + + J = 1 .
If we have
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ST3241 Categorical Data Analysis I
Models For Matched Pairs
Dependent Proportions and Conditional Models
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Example: Rating of Performance
For a poll of a random sample of 1600 votingage British
citizens, 944 indicated approval of the Prime mi
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ST3241 Categorical Data Analysis I
Two-way Contingency Tables
2 2 Tables, Relative Risks and Odds Ratios
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What Is A Contingency Table (p.16)
Suppose X and Y are two categorical variables
X has I categories
Y has J categories
Display the I
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ST3241 Categorical Data Analysis I
Two-way Contingency Tables
Odds Ratio and Tests of Independence
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Inference For Odds Ratio (p. 24)
For small to moderate sample size, the distribution of sample
odds ratio is highly skewed.
For = 1, cannot
Outline
1.1 Categorical Response Data
Chapter 1. Introduction: Distributions and
Inference for Categorical Data
1.2 Distributions for Categorical data
Deyuan Li
1.3 Statistical Inference for Categorical Data
School of Management, Fudan University
1.4
Outline
Chapter 2. Describing Contingency Tables
2.1 Probability Structure for Contingency Tables
2.2 Comparing Two Proportions
Deyuan Li
2.3 Partial Association in Stratied 2 2 Tables
School of Management, Fudan University
Feb. 28, 2011
2.4 Extension
Outline
3.1 Condence Intervals for Association Parameters
Chapter 3. Inference for Contingency Tables
3.2 Testing Independence in Two-way Contingency Tables
3.3 Following-up Chi-squared Tests
Deyuan Li
School of Management, Fudan University
3.4 Two-wa
Outline
12.1: Random eects modeling of a clustered categorical data;
Chapter 12. Random Eects: Generalized Linear
Mixed Models for Categorical Responses
12.2: Binary responses: logistic-normal model;
Deyuan Li
12.3: Examples of random eects models for
Statistics 101 Course Notes
Introduction to Quantitative Methods for
Psychology and the Behavioral Sciences
Instructor: Alan Agresti
Course syllabus: At top of course home page, which is also at
www.stat.ufl.edu/~aa/harvard
Teaching fellows:
Roee Gutman
J
ST3241 Categorical Data Analysis I
Semester II, 2012-2013
Solution to Tutorial 1
1. (a) Nominal.
(b) Ordinal.
(c) Ordinal.
(d) Nominal.
(e) Nominal.
2. As the student selects one answer randomly out of four possible choices, the prob- ability
that the stu
ST3241 Categorical Data Analysis I
Semester II, 2012-2013
Tutorial 7
1. For a study using logistic regression to examine the data on rheumatoid arthritis, we
consider age of the patient as the predictor variable. The response Y measured whether
the patien
ST3241 Categorical Data Analysis I
Semester II, 2012-2013
Tutorial 4
1. For baseball national league games during nine decades, the following table shows the
percentage of times that the starting pitcher pitched a complete game.
Decade
Percent
Complete
19
ST3241 Categorical Data Analysis I
Semester II, 2012-2013
Tutorial 6
1. The U.S. National Collegiate Athletic Association (NCAA) conducted a study of graduation rates for student athletes who were freshmen during the 19841985 academic year.
The following
ST3241 Categorical Data Analysis I
Semester II, 2012-2013
Tutorial 2
1. The following table was taken from the 1991 General Social Survey.
Belief in Afterlife
Race
Yes
No or Undecided
White
Black
621
89
239
42
(a) Identify each classification as a respons
ST3241 Categorical Data Analysis I
Semester II, 2012-2013
Tutorial 5
1. An experiment analyzes imperfection rates for two processes used to fabricate silicon wafers
for computer chips. For treatment A applied to 10 wafers, the numbers of imperfections
are
ST3241 Categorical Data Analysis I
Semester II, 2012-2013
Tutorial 8
1. To study the effects of racial characteristics on whether individual convicted of homicide
receive the death penalty, 674 subjects were classified in the following table.
Victims
Defe
ST3241 Categorical Data Analysis I
Semester II, 2012-2013
Tutorial 9
1. A study on educational aspirations of high school students (S. Crysdale, Int. J. Compar.
Sociol.,16:19 - 36 (1975) measured aspirations using the scale (some high school, high
school
ST3241 Categorical Data Analysis I
Semester II, 2012-2013
Tutorial 3
1. In murder trials in 20 Florida counties during 1976 and 1977, the death penalty was given
in 19 out of 151 cases in which a white killed a white, in 0 out of 9 cases in which a white
ST3241 Categorical Data Analysis I
Semester II, 2012-2013
Tutorial 1
1. Which scale of measurement is most appropriate for the following variables - nominal, or
ordinal?
(a) Political party affiliation (Democrat, Republican, unaffiliated).
(b) Highest deg