Spring 2006
Introduction to HLM6
Spring 2006 Quarter
Derby Hall 0125 (Basement Computer Lab)
Presenters: Roman Ivanchenko and Lyndsey Young
Post-Estimation Techniques in Statistical Analysis: Introduction to Clarify, S-Post, and Graphing in Stata
May 19, 2006
2:00-3:30pm
Derby Hall 0125 (Basement Computer Lab)
Presenters: Roman Ivanchenko and Lyndsey Young
Winter 2006
Introduction to R
February 17, 2006
9:30-11:00am
Derby Hall 0125 (Basement Computer Lab)
Presenters: Roman Ivanchenko and Lyndsey Young
Click here for the powerpoint presentation
Click here for the data files
STATA Data Management and Programming
January 20, 2006
9:30-11:00am
Derby Hall 0125 (Basement Computer Lab)
Presenters: Roman Ivanchenko and Lyndsey Young
Click here for the powerpoint presentation
Click here for the data files
Autumn 2005
Introduction to Stata
Friday, November 18, 2005
3:30 – 5:00 p.m.
Derby Hall 0125 (Basement Computer Lab)
Presenters: Sean Williams and Lyndsey Young
Click here for the powerpoint presentation
Spring 2005
Introduction to R
Tuesday, May 31, 2005
3:30 – 5:00 p.m.
Derby Hall 0125 (Basement Computer Lab)
Presenters: David Darmofal and Corwin Smidt
Presentation (in PDF)
Supporting Documents
Commands
Data
Winter 2005
Introduction to LaTeX
Thursday, February 17, 2005
3:30 – 5:00 p.m.
Derby Hall 0125 (Basement Computer Lab)
Presenters: Corwin Smidt and Zach Mears
Presentation (in PDF)
Supporting Documents
sections.tex sections.pdf
example.tex example.pdf
table.tex table.pdf
hello.tex hello.pdf
Autumn 2004
Post-Estimation Techniques in Statistical Analysis: Introduction to Clarify, S-Post, and Graphing in Stata
Tuesday, November 16, 2004
3:30 – 5:00 p.m.
Derby Hall 0150 (Basement Computer Lab)
Presenters: Dave Darmofal and Corwin Smidt
Clarify and S-Post Presentations (in PDF)
Introduction to Stata
Tuesday, October 5, 2004
2:00 – 3:30 p.m.
Derby Hall 0150 (Basement Computer Lab)
Presenter: Corwin Smidt
Presentation (in PDF)
Spring 2004
Saving Time With Prudent Data Management: Working with Data and Programming in Stata
The presentation is an overview of the resources and methods available to efficiently manage one’s data in Stata.
It covers general methods and tools such as generating variables, sorting variables, expanding and reshaping datasets, and
dealing with date and time functions. An introduction to programming within Stata follows with applications demonstrating its
benefits as a more efficient means of managing data.
Presenters: Brandon Bartels and Kevin Sweeney
Presentation (in PDF)
Advanced Programming in Stata
The presentation follows up on the introductory programming practices covered in the Saving Time With Prudent Data Management brownbag.
The first section instructs one on how one can program one’s own likelihood function, followed by the demonstration of specific
applications in Logit and Probit, Heteroskedastic regression, and split-population duration models. The second section introduces the
simulation programming capabilities of Stata with a focus on bootstrapping, Monte Carlo simulation, and programming post-estimation
simulations not covered by canned programs like Clarify.
Presenters: Kevin Sweeney and Brandon Bartels
Presentations1 and
2 (in PDF)
Teaching PS 585
This session was a PRISM hosted roundtable that encouraged faculty and graduate students to share their philosophies and strategies
in teaching the undergraduate-level research and statistical methods course. Syllabi were exchanged and those with experience in teaching
585 expressed what difficulties they have encountered, what strategies they have used, and what practices they felt worked.
Winter 2004
Introduction to Stata
Broad overviews of Stata, including information on getting started, as well as details on how to do basic data management, generate
descriptive statistics commands. The session is targeted to those who have never used Stata, but those who have a vague applied
understanding of Stata may also find the session useful.
Presenter: Kevin Sweeney
Presentation (in PDF)
Post-Estimation Techniques in Statistical Analysis: Introduction to Clarify & S-Post
Clarify (by Michael Tomz, Jason Wittenberg, and Gary King) and S-Post (by J. Scott Long), both free and easy to download software
packages, offer researchers the means of easily interpreting and presenting the effects of independent variables from maximum likelihood
models. Common post-estimation techniques include: 1) calculating the predicted probability of an event occurring given a covariate
profile; 2) calculating the change in the probability of an event occurring given a particular change in an independent variable of
interest (while holding other variables constant); and 3) producing various types of graphs, including the option of graphing the
probability of an event occurring as a function of a particular independent variable of interest (while holding other variables constant).
These techniques, among others, greatly aid an analyst in the most efficient and powerful presentation of results from a statistical
analysis.
Presenter: Brandon Bartels and Kevin Sweeney
Presentation (in PDF)
Endogeneity in Political Science Research: a panel on the issue of endogeneity in political science research.
Endogeneity exists in a model when an explanatory variable is not truly exogenous, but instead, is caused (or affected) by other
variables within the system. In general, unaccounted for reciprocal causation leads to biased results and potentially misleading inferences.
The panel examines endogeneity from three angles: as a theoretical issue, an issue of research design, and the issue of dealing with
endogeneity statistically and its possible problems.
Panelists: Professor Janet Box-Steffensmeier, Professor Dean Lacy, Professor Irfan Nooruddin,
Professor Brian Pollins, Brandon Bartels
