Sociology 382: Principles of Regression Analysis

rev: 12/20/2018

Syllabus 

Winter Quarter, 2019

Tuesdays and Thursdays,

10:30A-11:50A

Lathrop 294

 

Lab/Section once a week for homework and once a week for projects

 

Michael J. Rosenfeld

Professor

Department of Sociology

Building 120 room 124

mrosenfe@stanford.edu

The class website is my personal Stanford website

www.stanford.edu/~mrosenfe

Office Hours by appointment

 

TAs:

Elisa Kim

Austin van Loon

 

 

Introduction:

            In this class we will build on the basics of regression analysis we learned in Soc 381, and we will introduce some more advanced topics: Propensity Score Matching, Event History Analysis, the use of weights in regression, and Loglinear Models (also known as Poisson Regression). Most of the class work will be in Stata. We will also do some introductory work with R.

            Most class materials will be posted on my website (www.stanford.edu/~mrosenfe). We will use an online tool for collecting homework and returning homework, collecting and returning presentation drafts, collecting presentation slides, posting grades, and sending group emails.

 


Readings and Grading Policy

 

Books required (available at Stanford Bookstore):

* Treiman, Donald. 2009. Quantitative Analysis: Doing Social Research to Test Ideas. Jossey-Bass. ISBN-10: 0470380039. $59

* Silver, Nate. 2012. The Signal and the Noise: Why So Many Predictions Fail- But Some Don’t. ISBN-10: 0143125087. $16

* Plus various academic papers that will be required for reading and will be discussed on a particular class day

 

 

Recommended Books:

For loglinear models:

* Alan Agresti. 2018. Introduction to Categorical Data Analysis. Wiley. ISBN-10: 1119405262. $70.53

* Hout, Michael. 1983. Mobility Tables. Sage Press. ISBN-10: 0803920563. $22.

 

For Event History models:

* Yamaguchi, Kazuo. 1991. Event History Analysis. ISBN-10: 0803933231. Out of print but available used, and in the library

 

 

Recommended background books from last quarter

* Mathematical Statistics and Data Analysis, by John Rice, Duxbury Press, 3rd edition 2006, ISBN-10: 0534399428. $175

* Freedman, David, Robert Pisani, and Roger Purves. 2007. Statistics. Fourth Edition. W.W. Norton. $125. ISBN-10: 0393929728

 

 

The most important readings for the class are the Excel files, Stata logs, and PDF documentation posted on my website.

 

Software Required:

You should already have a STATA license. R and R Studio are free.

 

 

Students with Disabilities:

Students with Documented Disabilities: Students who may need an academic accommodation based on the impact of a disability must initiate the request with the Office of Accessible Education (OAE). Professional staff will evaluate the request with required documentation, recommend reasonable accommodations, and prepare an Accommodation Letter for faculty dated in the current quarter in which the request is made. Students should contact the OAE as soon as possible since timely notice is needed to coordinate accommodations. The OAE is located at 563 Salvatierra Walk (phone: 723-1066, URL: http://studentaffairs.stanford.edu/oae).          

 

Units:

This Course justifies an additional unit of credit, beyond what would be expected based on the typical assignment of class time and outside work. An additional unit represents, on average, 30 additional hours of work expected of a student during the quarter, devoted to homework and to the preparation of the student’s research presentation.

 

Computer Use Policy:

* Computer use by students during class is strictly limited to following along with the data analysis examples being presented by the professor.

 

 

 

 

 

Grading:

6 homeworks

90%

Regular class participation

5%

Regular section participation

5%

 

 

 

Project and Reading Assignment Timeline

(Note: my chapter and section headings for Rice are from the 2nd edition; the same material should be in the 3rd edition but you may have to look for it).

 

Week

CLASS

READING (Readings in bold are required and will be discussed specifically in that class. Other readings are supplementary)

ASSIGNMENT

1

January 8

 

 

 

January 10

 

 

 

 

 

 

2

January 15

Read Nate Silver’s Signal and the Noise in its entirety (required)

 

 

January 17

Trieman’s chapter 12 on loglinear analysis (required).

 

HW 1 due

 

 

 

 

3

January 22

 

 

 

January 24

 

HW 2 due

 

 

 

 

4

Jan 29

 

 

 

Jan 31

 

HW3 due

 

 

 

 

5

Feb 5

 

 

Feb 7

Read Cohen “The Earth is Round” on Bayesian Analysis (required) and Read Lisse et al on Vioxx (Rofecoxib), and the importance of Power in tests (both linked on my website).

 

 

section

 

 

 

 

 

 

6

Feb 12

R learning boot camp in class or in the library

 

 

Feb 14

R learning boot camp in class or in the library

 

 

 

 

 

7

Feb 19

Yamaguchi’s Event History Analysis, chapters 1 and 2

 

 

Feb 21

HW 4 due

 

 

 

8

Feb 26

 

 

 

Feb 28

 

 

 

 

 

 

 9

March 5

 

HW 5 due

 

March 7

 

 

 

 

 

 10

March 12

 

 

 

March 14

 

HW 6 due