NOTES:
This web page is under development. Links will become live when they are
ready. Click
here if you want to see the online notes and
handouts from the last time the course was taught. Some of these will be updated for this course.
My notes from Graduate Statistics I are also
available.
My
Stata Highlights
page includes links to Stata and statistical handouts from my other courses that
may interest readers.
Stata and SPSS are in the labs. You can also order your own personal copy of Stata
through the
GradPlan
package. I recommend the Intercooled Stata 10 & Getting Started Manual for
$155. Cheaper and more expensive packages are also available. You
can get by with Stata 9 if you already have it, but the data file format changed
in Stata 10 so that may occasionally cause you problems if you are using an
older version.
The following special types of files are used on this web page:
 |
Pdf files. Require Adobe Acrobat.
 |
 |
Toolbook files.
 |
 |
SPSSWIN files. Necessary for doing homework problems. Can probably be
adapted for other SPSS platforms. You should save these files to your local hard disk and
then use them with SPSS. |
 |
Stata 9 & 10 files. Necessary for
doing homework problems.You should save these files to your local
hard disk and then use them with Stata. |
In addition, some files are in zipped (compressed) format. If you
don't have an unzipping program (e.g. Winzip), you can use the free PC Magazine PCDEZIP
utility.
Finally, please note that the answer keys for the exams and homework
differ in the amount of detail provided. I sometimes give very detailed answers,
other times the answers are much more minimal (and given the information provided I assume
the student can figure out the rest). Students should always aim for complete
answers in their homework and exams. In particular, it is hard to give partial
credit when it is not clear why an error was made.
Syllabus
Readings Packet (You need a Notre
Dame NETID to access these)
Example First Draft - Karen
Boyd, 2002 (Used with Permission)
Example First Draft -
Selected RW comments on Boyd Draft
Notre Dame's Social Research Data Services
Web Page (has links to several data sets and
describes support services)
Useful sites
for learning about Stata and SPSS
PART I: In this section, we briefly review the basics of OLS regression. We
talk about some of the most common issues (measurement error, missing data, violations of
OLS assumptions) encountered in regression analysis.
Using SPSS for OLS Regression
(Read on your own & ask questions in Lab as needed)
reg01.sav -
Data file used in the SPSS Regression handout
Using Stata for OLS Regression
(Read on your own & ask questions in Lab as needed)
reg01.dta - Data
file used in the Stata Regression handout
Overview
Review
of Multiple Regression
Homework # 1 (Due Jan 28)
sphrd.dta (Stata data file required for
HW # 1)
Homework
# 1 Answer Key
Multicollinearity
mulicoll.dta -
Stata data
file used in the Multicollinearity handout
Missing
Data
md.dta - Stata
data file used in the Missing Data handout
Homework # 2 (Due Feb
4)
longley.dta
missing.sps
missing.sav
missing.dta
Homework
# 2 Answer Key
missing-ak.sps
(adds some additional analyses to the earlier program)
hw02-III.do (Stata program for problem
3)
Measurement
Error
Measurement
Error Example (Supplemental)
Scale Construction (Very Brief
Overview)
anomia.dta -
Stata data file used in the Scale Construction handout
anomia.sav -
SPSS data file used in the Scale Construction handout
Outliers
outliers.dta -
Stata data file used in the Outliers handout
outliers.sav -
SPSS data file used in the Outliers handout
Also Recommended: Robert Yaffee's
Robust Regression
Modeling with Stata (This is 93 pages long but it is basically overhead
slides and hence much shorter than it at first appears to be. Nice
discussions of how to deal with outliers and with heteroskedasticity.)
Heteroskedasticity
reg01.dta -
Stata data file used in the Heteroskedasticity handout
Serial Correlation (Very Brief
Overview)
Also Recommended:
UCLA's Regression Diagnostics Page.
Shows a lot of the techniques that are available with Stata for
detecting outliers, heteroskedasticity, multicollinearity, serial correlation and other problems with regression models.
Homework # 3 (Due Feb 11)
resales.dta
resales.sav
Homework
# 3 Answer Key
resales.do (Stata program for the real
estate sales problem)
resales.sps (Spss
Program for the real estate sales problem)
Sample first exams
and answer keys
PART II: This section shows how regression can be used to properly specify a
causal model. We begin by introducing "the logic of causal order," which lets us
understand the different kinds of causal relationships that might be present between
variables. Common model mis-specifications are then addressed (e.g. omitted variables,
extraneous variables, variables with nonlinear effects). We discuss how to choose between
alternative causal models. Finally, we introduce path analysis as a method for causal
modeling.
tbklogic.zip
These are toolbook presentations which we will go over in
class.
[Optional] If you also want more conventional notes for the above material,
click here and
here. In class, I'll only use these notes if there is a problem with the Toolbook presentation.
Local of Causal Order, Handout 1:
Variable Naming
Local of Causal Order, Handout
2: Sample Problem, Logic of Causal Order
Local of Causal Order, Handout
3: Suppressor Effects
Local of Causal Order, Handout
4: Interaction Effects
Local of Causal Order, Handout
5: Another Sample Problem for the Logic of Causal Order
The Logic of Causal Order, Closing Comments
Homework # 4 (due Feb 25)
Homework
# 4 Answer Key
Specification
Error
Imposing
and Testing Equality Constraints
in Models
blwh.dta - Stata data
file used in the constraints & group comparisons handouts
Group Comparisons: Differences
in Composition Versus Differences in Models and Effects
Group Comparisons: Using "What
If" Scenarios to Decompose Differences Across Groups
Homework # 5 (Due March 4)
gender.dta
gender.sav
Homework
# 5 Answer Key
Interaction
Effects and Group Comparisons
Models for Group Comparisons -
Summary
blwh.dta -
Stata data file used in the Interaction Effects handout
Interpreting Interaction
Effects; Interaction
Effects and Centering
drinking.dta -
Stata data file used in the Interpreting Interaction Effects handout
Discussion Questions for Group
Comparisons and Interaction Effects (Cover these on your own if we don't
get to them in class)
Interactions
Between Continuous Variables (Read on your own if we
don't get to it in class)
Homework # 6
(Due March 18)
gender.dta
gender.sav
jgqes2.sps
jgqes2.sav
Homework
# 6 Answer Key
Nonlinear
Relationships
Introduction
to Path Analysis
Introduction
to Path Analysis - Highlights
Homework # 7 (Due March 25)
nonlinhw.sps
nonlinhw.sav
Homework
# 7 Answer Key
Sample second exams
and answer keys
PART III: Here, we develop path analysis techniques more fully. We talk about
more complicated models that cannot be accurately estimated through conventional OLS
regression techniques (e.g. nonrecursive models). We also talk about situations where the
nature of the data make OLS regression inappropriate (e.g. dichotomous dependent
variables) or less than optimal.
Structural
Coefficients in Recursive Models/ Evils of Standardization
Computing
R Square/ Evils of R Square
Homework # 8
(Due April 8)
evilstnd.sps
Homework
# 8 Answer Key
Logistic
Regression I: Problems with the Linear Probability Model (LPM)
Logistic
Regression II: The Logistic Regression Model (LRM)
Logistic
Regression III: Hypothesis Testing, Comparisons with OLS
Using Stata for Logistic Regression
(be sure to read this on your own, as it covers important details we may not
go over in class)
logist.dta -
Stata data file used in the Logistic Regression handout
Homework #
9 (Due April 15)
lrb.sps
lrb.sav
lrcalc.sps
lrb.dta
Homework #
9 Answer Key
Ordered Logit Models
Multinomial
Logit Models
shuttle2.dta -
Stata data file used in the Ordered Logit and Multinomial Logit handout
Nonrecursive Models
nonrecur.dta -
Stata data file used in the Nonrecursive Models handout
Brief Overview of Manova
blwh.dta -
Stata data file used in the Manova handout
Brief Overview of LISREL
Extremely Brief Overviews of Event History
Analysis and Hierarchical Linear Modeling --
Read Ch. 9 of Paul Allison's Multiple Regression Primer,
paying particular attention to section 9.9 (Multilevel Models) and section
9.12 (Event History Analysis)
Homework #
10 (Due April 29)
Homework
# 10 Answer Key
Sample final exams
and answer keys
Other materials may be available upon
request.
