Sociology 709, Applied
Regression Analysis
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.
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Month |
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Topic |
Fox |
Kennedy |
Before Class Reading
Assignment |
Lecture notes & reading
notes |
Problem Set |
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Jan |
11 |
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16 |
1 |
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1,2 |
1 |
Fox
Ch1 p 3-14, Ch 2 p 15-24 Kennedy
Ch1 p 1-9 |
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18 |
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5.1 |
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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?) |
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23 |
2 |
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5.2-5.3 |
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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 |
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25 |
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2 |
NWK,
p.52-54 (Normal Error Regression Model
& Estimation by Maximum Likelihood) Kennedy
Ch 2 p 9-26 |
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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 |
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Feb |
1 |
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Fox Ch 6 p. 120-130 Kennedy Ch 3 p 60-66 |
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6 |
4 |
Statistical theory for
linear models |
9.1-9.3 |
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Fox
Ch 9 p. 204-205.5 (i.e. include the top half of 206), 212-216.5 Scott
Lynch, Matrix Algebra Review |
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8 |
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Fox
Ch 9 p. 216.5-222 |
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13 |
5 |
Dummy variables |
7 |
14 |
Fox
Ch 7 p. 135-152 Kennedy p. 248-257 |
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15 |
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ANOVA |
8 |
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Fox
Ch 8 p. 155-178 |
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20 |
6 |
Qualitative dependent
variables I |
15 |
15 |
Fox
Ch 15 p. 438-448 Kennedy
Ch 15 |
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22 |
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Continue
Lecture K |
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27 |
7 |
Review & exam |
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Review |
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Mar |
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Midterm
Exam |
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6 |
8 |
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Continue
Lecture K, Logit Models |
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8 |
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Qualitative dependent
variables, II |
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Categorical
variables with multiple categories |
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20 |
9 |
Influential cases |
11 |
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Unusual
and influential data Fox
p. 267-286. |
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22 |
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Specification and Omitted
Variable Bias |
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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) |
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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] |
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29 |
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Multicollinearity |
13 |
11 |
Baum 84-87 (on reserve) Kennedy 205-212 |
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April |
3 |
11 |
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Catchup |
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Weighting data |
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Stata User’s Guide,
weights (on reserve) CPC
Stata guide “choosing the correct weight syntax” |
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10 |
12 |
Missing Data |
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Paul Allison, Missing Data, Chapters 1-3 & 5. (pages 1-14, 30-38), on reserve. |
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12 |
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Longitudinal data, (fixed effects and random effects models) |
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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) |
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17 |
13 |
Maximum likelihood |
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Eliason, Maximum Likelihood
Estimation, (p. 1-17, pages 39-45 optional)
(on reserve) |
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19 |
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Causality, simultaneous
equation models and problems |
16 |
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Optional:
Denis
and Legerski, Causal Modeling and the Origins of Path Analysis |
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24 |
14 |
Multi-level models |
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Lec
Z |
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26 |
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Review |
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Take-home final exam, practice version |
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Topics to cover in the
future: Bootstrap methods |
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