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 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.
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 Center for Social Research (has links to several data sets and describes support services)
Dropbox. I strongly encourage you to set up a Dropbox account if you do not already have one. Dropbox gives you a minimum of 2GB of free online storage. More critically, with Dropbox you can set up shared folders. This makes it much easier when you want me or others to help you with your research. You can create a folder, put your data and programs in it, and then share the folder with me. If you set up an account use your .edu email address because you can get more bonus storage that way. For more click on this link.
Useful sites for learning about Stata and SPSS
UCLA's Statistical Computing Resources RW Suggestions for Using Stata at Notre Dame UCLA's SPSS Starter Kit Resources for learning Stata UCLA - How does Stata compare with SAS and SPSS? The Stata User Support Page Ben Jann's estout/esttab support page (esttab & estout are great for formatting output from Stata)
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 9 & and higher for OLS Regression (Read on your own & ask questions in Lab as needed.)
reg01.dta - Data file used in the Stata Regression handout
Review of Multiple Regression
Homework # 1 (Due Feb 1)
sphrd.dta (Stata data file required for HW # 1)
Homework # 1 Answer Key
mulicoll.dta - Stata data file used in the Multicollinearity handout
md.dta - Stata data file used in the Missing Data handout & in the homework
Homework # 2 (Due Feb 8)
Homework # 2 Answer Key
missingx.do (Additional Stata Analyses)
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.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.)
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 15)
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. [NOTE: You may have trouble using this with Win 7. I did with Win7 64 bit. But it can be done. If you really want to do so I can tell you how to do it.]
[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 29)
Homework # 4 Answer Key
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 7)
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
Interactions Between Continuous Variables (Read on your own if we don't get to it in class)
Homework # 6 (Due March 21)
Homework # 6 Answer Key
Introduction to Path Analysis
Introduction to Path Analysis - Highlights
Homework # 7 (Due March 28)
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 11)
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
[Optional] Logistic Regression III using SPSS (This is an old version of the handout from the course's old SPSS days)
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 25)
Homework # 9 Answer Key
Brief Overview of Survey Data Analysis. By default, most statistical techniques assume that data were collected via simple random sampling. This is often not true for large national data sets. Fortunately, Stata makes it easy to analyze such data, but there are some important differences in how you go about testing hypotheses and assessing model fit.
Introduction to Survey Data Analysis (From the Stata 12 documentation; read the first few pages carefully and skim the rest)
Analyzing Survey Data: Some Key Issues to be Aware of
UCLA's (see lower third of page) and StataCorp's FAQS on Survey Data Analysis (Optional; you may want to refer to these if you use the SVY commands)
Brief Overview of Other Advanced Methods.
Brief Overview of Panel Data
Brief Overview of Manova
blwh.dta - Stata data file used in the Manova handout
Brief Overview of Structural Equation Modeling using Stata's sem commands
Brief Overview of Structural Equation Modeling using LISREL (Optional; you can read this if you ever happen to be using LISREL
Nonrecursive Models (Highlights)
Nonrecursive Models (Optional Long Version) This is an older version of the handout that has much more detail if you want it; the highlights version is probably all you need in practice, at least for a basic understanding.
nonrecur.dta - Stata data file used in the Nonrecursive Models handouts
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)
Advanced Categorical Data Methods. We will only cover these in class if time permits, but skim through them on your own. These are covered in much more depth in Soc 73994, Categorical Data Analysis.
Ordered Logit Models
Multinomial Logit Models
shuttle2.dta - Stata data file used in the Ordered Logit and Multinomial Logit handout
Homework # 10 (Due May 2)
Homework # 10 Answer Key
Sample final exams and answer keys
Other materials may be available upon request.