Updated 4/27/07 8:44 AM

Sociology 709, Applied Regression Analysis

Schedule of Topics, Reading Assignments, and Reading Notes

 

Textbooks:  Peter Kennedy, A Guide To Econometrics, 5th edition.

            John Fox, Applied Regression Analysis, Linear Models, and Related Methods

 

 

Note:  The official schedule is the web page.  Refer to this online schedule page before preparing for each class.

 

Month

Date

Week#

Topic

Fox

Kennedy

Before Class Reading Assignment

Lecture notes & reading notes

Problem Set

Jan

11

 

 

 

 

 

Lec A

Stata1

 

 

16

1

Introduction, Stata

1,2

1

Fox Ch1 p 3-14, Ch 2 p 15-24

Kennedy Ch1 p 1-9

Lec B

 

 

 

18

 

Simple bivariate regression

5.1

 

Fox Ch 5 p 85-94

Allison, Multiple Regression: A Primer p. 2-14 (“What is Multiple Regression”) and  p.97-108  (How does Bivariate Regression Work?)

 

Lec C

 

 

PS1

 

23

2

Multivariate Regression

5.2-5.3

 

Fox Ch 5 p 97-108

Allison, Multiple Regression: A Primer. p.15-48 (“How do I interpret Multiple Regression Results”)

Multiple regression: Stata examples

 

Lec E

 

 

25

 

 

 

2

NWK, p.52-54  (Normal Error Regression Model & Estimation by Maximum Likelihood)

Kennedy Ch 2 p 9-26

 

 

Lec D

 

PS2

 

30

3

Statistical inference

6

3, 4

Fox Ch 6 p. 112-118 (Statistical inference for regression, simple regression)

Kennedy Ch 3 p 47-59

 

Lec F

 

Feb

1

 

 

 

 

Fox Ch 6 p. 120-130

Kennedy Ch 3 p 60-66

 

Lec G

PS3

 

6

4

Statistical theory for linear models

9.1-9.3

 

Fox Ch 9 p. 204-205.5 (i.e. include the top half of 206), 212-216.5

Scott Lynch, Matrix Algebra Review

 

Lec H1

 

 

8

 

 

 

 

Fox Ch 9 p. 216.5-222

 

Lec H2

 

PS4

 

13

5

Dummy variables

7

14

Fox Ch 7 p. 135-152

Kennedy  p. 248-257

Lec I

 

PS5

 

15

 

ANOVA

8

 

Fox Ch 8 p. 155-178

 

 

 

Lec J

 

 

20

6

Qualitative dependent variables I

15

15

Fox Ch 15 p. 438-448

Kennedy Ch 15

 

Lec K

 

 

22

 

 

 

 

Continue Lecture K

 

PS6

 

27

7

Review & exam

 

 

Review

Exam review sheet

 

 

Mar

1

 

 

 

 

Midterm Exam

Midterm 1, Spring 2007

Midterm 2, Spring 2007

 

 

 

6

8

 

 

 

Continue Lecture K, Logit Models

 

 

 

8

 

Qualitative dependent variables, II

 

 

Categorical variables with multiple categories

Lec L

 

 

20

9

Influential cases

11

 

Unusual and influential data

Fox p. 267-286.

Lec P

 

 

22

 

Specification and Omitted Variable Bias

 

5,6

Gronniger, “Familial Obesity As A Proxy For Omitted Variables In The Obesity-Mortality

Relationship”, Demography, Volume 42-Number 4, November 2005: 719-735

[Note: this article is on reserve]

 

Kennedy, Chapter 5 (p. 81-86, 92-99), Chapter 6 (p.107-109, 114-116)

 

Lec Q

PS7

 

27

10

Problems with the error term

12

7,8,9

Fox (p. 301-306)

Baum, An Introduction to Modern Data Analysis using Stata, (p.133-149) [Note: This article is on reserve]

Lec R

 

 

29

 

Multicollinearity

13

11

Baum 84-87 (on reserve)

Kennedy 205-212

 

Lec S

PS8

April

3

11

 

 

 

Catchup

 

 

 

5

 

Weighting data

 

 

Stata User’s Guide, weights (on reserve)

 

CPC Stata guide “choosing the correct weight syntax”

 

Answer key (do-files) for PS8

 

Lec T

 

PS9

 

10

12

Missing Data

 

 

Paul Allison, Missing Data, Chapters 1-3 & 5. (pages 1-14, 30-38), on reserve.

 

 

Lec U

 

 

12

 

Longitudinal data,  (fixed effects and random effects models)

 

10

Explaining Occupational Sex Segregation and Wages: Findings from a Model with

Fixed Effects, Paula England; George Farkas; Barbara Stanek Kilbourne; Thomas Dou, ASR, Vol. 53, No. 4. (on reserve, jstor link)

 

Kennedy, p.301-307

Baum 220-231 (on reserve)

 

Lec V

PS10

 

17

13

Maximum likelihood

 

 

Eliason, Maximum Likelihood Estimation, (p. 1-17, pages 39-45 optional)  (on reserve)

 

Lec X

 

 

19

 

Causality, simultaneous equation models and problems

16

 

Optional: Denis and Legerski, Causal Modeling and the Origins of Path Analysis

Lec Y

 

 

24

14

Multi-level models

 

 

 

Lec Z

 

 

26

 

Review

 

 

Review sheet for the final exam

 

 

 

 

 

 

 

 

Take-home final exam,  practice version

Practice data #1,  Practice data #2

Practice do-file, log-file

 

 

 

 

 

 

 

 

 

Take home final, final version

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Topics to cover in the future:

Bootstrap methods