advanced diagnostics for multiple regression analysis

Table of Contents
INTRODUCTION 1 CHAPTER ONE 7 CHAPTER TWO 20 CHAPTER THREE 36 CHAPTER FOUR 49 ADVANCED DIAGNOSTICS FOR MULTIPLE REGRESSION ANALYSIS 66 CHAPTER FIVE 69 CHAPTER SIX 89 CHAPTER SEVEN 100 CHAPTER EIGHT 116 CHAPTER NINE 127 CHAPTER TEN 142 CHAPTER ELEVEN 152 CHAPTER TWELVE 167 SAMPLE MULTIPLE CHOICE QUESTIONS 175 INTRODUCTION
This manual has been designed to provide teachers using Multivariate Data
Analysis, 6th edition, with supplementary teaching aids. The course
suggestions made here are the result of years of experience teaching the
basic content of this text in several universities. Obviously, the contents
may be modified to suit the level of the students and the length of the
term. Multivariate data analysis is an interesting and challenging subject to
teach. As an instructor, your objective is to direct your students'
energies and interests so that they can learn the concepts and principles
underlying the various techniques. You will also want to help your students
learn to apply the techniques. Through years of teaching multivariate
analysis, we have learned that the most effective approach to teaching the
techniques is to provide the students with real-world data and have them
manipulate the variables using several different programs and techniques.
The text is designed to facilitate this approach, making available several
data sets for analysis. Moreover, accompanying sample output and control
cards are provided to supplement the analyses discussed in the text. WHAT'S NEW AND WHAT'S CHANGED The sixth edition has many substantial changes from prior editions that we
feel will markedly improve the text for both faculty member and student.
Three notable additions were made to the text: . The most obvious change in the sixth edition is the new database-
HBAT. The emphasis on improved measurement, particularly multi-item
constructs, led us to develop HBAT. After substantial testing we
believe it provides an expanded teaching tool with various
techniques that are comparable to the HATCO database, which will
still be available on the book's Web site.
. A second major addition is "Rules of Thumb" for the application and
interpretation of the various techniques. The rules of thumb are
highlighted throughout the chapters to facilitate their use. We are
confident these guidelines will facilitate your utilization of the
techniques. . A third major change to the text is a substantial expansion in
coverage of structural equations modeling. We now have three
chapters on this increasingly important technique. Chapter 10
provides an overview of structural equation modeling, Chapter 11
focuses on confirmatory factor analysis, and Chapter 12 covers
issues in estimating structural models. These three chapters
provide a comprehensive introduction to this technique.
Each chapter has been revised to incorporate advances in technology, and
several chapters have undergone more extensive change: . Chapter 2 "Examining the Data" has an expanded section on missing
data assessment, including a flowchart depicting a series of
decisions that are involved in identifying and then accommodating
missing data.
. Chapter 5, "Multiple Discriminant Analysis and Logistic
Regression," provides complete coverage of analysis of categorical
dependent variables, including both discriminant analysis and
logistic regression. An expanded discussion of logistic regression
includes an illustrative example using the HBAT database.
. Chapter 7, "Conjoint Analysis," has a revised examination of issues
of research design that focuses on the development of the conjoint
stimuli in a concise and straightforward manner. An important development is the continuation of the Web site "Great Ideas
in Teaching Multivariate Statistics" at www.mvstats.com, which can also be
accessed as the Companion Web site at www.prenhall.com/hair. This Web site
acts as a resource center for the textbook as well as everyone interested
in multivariate analysis, providing links to resources for each technique
as well as a forum for identifying new topics or statistical methods. In
this way we can provide more timely feedback to researchers than if they
were to wait for a new edition of the book. We also plan for the Web site
to be a clearinghouse for materials on teaching multivariate statistics-
providing exercises, datasets, and project ideas. ORGANIZATION OF THE CHAPTERS IN THE TEXT The text is designed to help make your teaching as enjoyable and as simple
as possible. Each chapter begins with a "Chapter Preview" so that students
will understand the major concepts they are expected to learn. To
facilitate understanding of the chapter material and as a ready reference
for clarification, definitions of key terms are presented at the front of
each chapter. The text is designed for those individuals who want to obtain
a conceptual understanding of multivariate methods-what they can do, when
they should be used, and how the results should be interpreted. Following this design, each chapter is structured in a step-by-step manner,
including six steps. The end of each chapter includes an illustration of
how to apply and interpret each technique. Basically, the approach is for
the "data analyst," therefore, the math formulae and symbols are minimized.
We believe it is the most practical, readable guide available to
understanding and applying these otherwise complex statistical tools. At
the end of each chapter, we review the Learning Objectives to provide the
student with an overview of what has been covered in the chapter in
relation to those major concepts or issues defined in the Learning
Objectives. Finally, a series of questions is provided to stimulate the
student to evaluate what has been read and to translate this material into
a workable knowledge base for use in future applications. ORGANIZATION OF THE CHAPTER MATERIALS This instructor's manual is designed to facilitate the preparation and
conduct of classes, exams, and seminars. Materials included in the manual
are organized in two sections for each chapter. (1) Chapter summaries: to refresh the instructor's memory without the
necessity of re-reading the entire chapter prior to class. Each chapter
summary is organized around four major sections. The objective of these
sections is to identify particular issues that may be useful in organizing
class discussion. The four sections are: a. What - an overview, or brief description, of the technique. b. Why - a description of the basic objectives of the technique. c. When - identification of the types of problems the technique may be
used to address. d. How - description of the assumptions applicable to the technique,
the data requirements for its use, the major points which are
essential to the successful implementation of the research plan
and the key points contained in the computer output needed for a
complete and accurate interpretation of the results. (2) Answers to the end-of-chapter questions: suggested answers to the
questions that can form the basis for further elaboration if desired. Sample exam questions: while essay or short answer questions are probably
preferable for examinations, many times multiple choice questions can be
used as a method for assessing specific knowledge about the subject. To
ease the burden of writing exam questions, multiple choice questions are
provided for each chapter. All of the sample exam questions have been
placed in a separate section at the end of the Instructor's Manual.
THE COMPANION WEB SITE - MVSTATS.COM The authors have established a Web site entitled "Great Ideas in Teaching
Multivariate Statistics" with the objective of providing a clearinghouse
for instructional materials and a forum for discussions about pedagogical
issues. Accessed directly at www.mvstats.com or through the Companion Web
site link at the Prentice-Hall Web site (www.prenhall.com/hair), the Web
site will offer all of the supplementary materials for the text (datasets,
control card files and output files) as well as links to additional
datasets for use in class and Web-based materials for each technique. A
complete set of datasets and related materials are available not only for
the sixth edition, but the fifth edition (HATCO dataset) as well. We
sponsor a mailing list MVSTAT-L that is open to the interested participants
for asking questions related to either the teaching or application of
multivariate statistics. An important adjunct is a "faculty-only" section of the Web site where
additional pedagogical materials will be made available to all adopters of
the textbook. The permission-based section will allow for providing the
text-related materials (e.g., PowerPoint slides and image files of all
figures in the text) as well as acting as a forum for faculty interested in
teaching multivariate statistics. We encourage any faculty member to
contribute to the mailing list or even contribute class-related materials
which we will disseminate among all those interested in the subject area.
We envision this to be an evolutionary project, with its growth and focus
guided primarily by its users and contributors. We hope that we c