2012 Syllabi and Reading Lists

Syllabi have been provided in PDF format, and require Adobe Acrobat Reader in order to viewed. If you do not have Acrobat Reader installed on your computer, you may obtain a free copy from Adobe's website.

Advanced Bayesian Models for the Social Sciences - Skyler Cranmer and Jong Hee Park

Advanced Game Theory - James D. Morrow

Advanced Multivariate Statistical Methods - Robert A. Henson

Advanced Topics in Maximum Likelihood Estimation - Bradford Jones and David Darmofal

Analyzing Developmental Trajectories (Amherst, MA) - Daniel Nagin

Analyzing Multilevel & Mixed Models Using Stata - William Rising

Applied Data Science: Managing Research Data for Re-Use - Jared Lyle, Kathleen Fear, Mary Vardigan, Jake Carlson

Applied Multilevel Models w/SAS-SPSS (Boulder, CO) - Lesa Hoffman

Applied Multilevel Models - Patricia McManus

Assessing and Mitigating Disclosure Risk: Essentials for Social Scientists - JoAnne O'Rourke

Categorical Data Analysis - Shawna Smith

Causal Inference for the Social Sciences - Ben Hansen and Ryan T. Moore

Causal Inference in the Social Sciences: Matching, Propensity Scores, and Other Strategies (Berkeley, CA) - Dominik Hangartner and Marco Steenbergen

Complex Systems Models in the Social Sciences - Kyle Joyce, Daniel Katz, Kenneth Kollman, Scott de Marchi and Aaron Bramson

Data Mining (Hubert M. Blalock Memorial Lecture Series) - Robert Stine

Designing, Conducting, and Analyzing Field Experiments - Donald P. Green

Doing Bayesian Data Analysis: An Introduction - John Kruschke

Growth Mixture Models: SEM (Chapel Hill, NC) - Sarah Mustillo

Health Disparities Research and Minority Populations: Exploring ICPSR Data Sources - Paula Braveman, University of California, David R. Williams, Patrick Krueger, Gabriel Sanchez and John Garcia

Hierarchical Linear Models for Longitudinal Data (Boulder, CO) - Aline Sayer

Hierarchical Linear Models I (Amherst, MA) - Mark Manning and Aline Sayer

Introduction to Applied Bayesian Modeling for the Social Sciences - Ryan Bakker

Introduction to Computing - Michael Hawthorne

Introduction to Computing Second Session - Michael Hawthorne

Introduction to Game Theory - Scott H. Ainsworth

Item Response Theory (Boulder, CO) - Jonathan Templin

Latent Growth Curve Models (LGCM): A Structural Equation Modeling Approach (Chapel Hill, NC) - Kenneth Bollen

Longitudinal Analysis - Michael Berbaum

Longitudinal Data Analysis, including Categorical Outcomes - Donald Hedeker

Mathematics for Social Scientists I - Stephen Bringardner

Mathematics for Social Scientists II - Howard Thompson

Mathematics for Social Scientists III - Don Eckford

Maximum Likelihood Estimation for Generalized Linear Models - Dean Lacy

Methodological Issues in Quantitative Research on Race and Ethnicity - Abigail Sewell

Military Nursing Research: Fundamentals of Survey Methodology - James Lepkowski and Philip Brenner

Missing Data: Intro (Bloomington, IN) - Tenko Raykov

Missing Data: Statistical Analysis of Data with Incomplete Observations (Hubert M. Blalock Memorial Lecture Series) - Tenko Raykov

Mixed Methods: Approaches for Combining Qualitative and Quantitative Research Strategies (Chapel Hill) - John W. Creswell, Jennifer Wisdom and Paul D. Mihas

Models for Categorical Outcomes Using Stata: Specification, Estimation, and Interpretation - J. Scott Long

The National Black Election/Politics Studies: Use and Analysis - Ronald E. Brown

Network Analysis - Ann McCranie

Network Analysis: A Second Course - Stanley Wasserman and Hank Green

Network Analysis: Advanced Topics - Bruce Desmarais

Network Analysis: An Introduction - Stanley Wasserman and Hank Green

Network Analysis: Theory/Methods (Bloomington, IN) - Ann McCranie and Bernice Pescosolido

Analysis of Large-Scale Networks - Jukka-Pekka Onnela

Panel Data Analysis Using Stata - David Drukker

Providing Social Science Data Services - Chuck Humphrey, James Jacob and JakeCarlson

Quantitative Analysis of Crime & Criminal Justice - Lynn Addington

R Statistical Computing Environment - John Fox

The R Statistical Computing Environment: The Basics and Beyond (Berkeley, CA) - John Fox

Rational Choice Theories of Politics and Society - James Johnson

Regression Analysis I: Introduction - Saundra Schneider

Regression Analysis II: Linear Models - Timothy McDaniel

Regression Analysis II: Linear Models - Brian Pollins

Regression Analysis III: Advanced Methods - David Armstrong

Introduction to the R Statistical Computing Environment - David Armstrong and John Fox

Review/Introductory Lectures on Matrix Algebra - Pedro Sanchez

Simultaneous Equation Models - Sandy Marquart-Pyatt

Social Network Analysis: An Introduction (Chapel Hill, NC) - Professor Katherine Faust

Spatial Econometrics: Statistical Models of Interdependence Among Observations - Robert J. Franzese

Introduction to Spatial Regression Analysis (Chapel Hill) - Paul Voss and Katherine J. Curtis

Introduction to Statistics and Data Analysis I - Pedro Sanchez

Introduction to Statistics and Data Analysis II - Lok-Sze Wong

Structural Equation Models With Latent Variables - Douglas Baer

Structural Equation Models and Latent Variables: An Introduction - Kenneth Bollen

Time Series Analysis - Sara Mitchell

Time Series Analysis: A Second Course - Harold D. Clarke

Time Series Analysis: Advanced Topics - Mark Pickup and Patrick Brandt

Time Series Analysis: An Introduction for Social Scientists - Mark Pickup

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