Causal Inference (Master Course, PSMM-1)

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Place and time
Second semester, period two, week 16 – 22, 2009
Wednesday's from 13.00 – 15.00 hours in room 0061 of the Munting Building
The first meeting is on April 15

Purpose
To get acquainted with principles of causal inference, and to obtain an overview of statistical techniques that can be used to estimate causal effects in experimental and observational studies.

Global content
Causal inferences play a predominant role in science. Yet the problems encountered in the process of trying to attain causal explanations are often severe, especially in the social and behavioral sciences. Basic elements of causal inference and the consequences for experimental and non-experimental research designs are covered in this course. Special attention will be given to causal inference in observational studies and to up-to-date statistical methods that are available in the search for causal explanations in the social sciences.

Lectures and literature
There will be seven lectures of two hours once a week. A rather provisional list of lectures and corresponding literature is available online. By the first week of April, a reader with literature under the title Causal Inference in Experiments and Observational Studies will be available at the Service Desk of the Reproduction Office. The books shown at the top of this page are

• Rubin, D.B. (2006). Matched sampling for causal effects. Cambridge: Cambridge University Press.
  
  
• Rosenbaum, P.R. (2002). Observational studies (2nd ed.). New York: Springer.
  
  

Practical work
Depending on a number of factors there might be weekly Causal Lab assignments. After week five, a full afternoon session will be organized on matching algorithms and practical exercises with R software; details follow in due time.

Evaluation and exams
Conditional assignment work, and a written exam at the end of the course. The first written exam is on Friday June 12, 2009, from 09.00–11.00 hours in the Exam Hall, Zernikelaan 7. A second opportunity for this exam is offered on Thursday July 2, 2009, from 09.00–11.00 hours, Room 0061 of the Muntingh Building.

Credit points
The number of credit points to be obtained equals five EC.

Questions and remarks
For questions and remarks one may contact the lecturer A. Boomsma, Grote Rozenstraat 31, room 0110, telephone (363)6187, e-mail a.boomsma@rug.nl.


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• Some Historical Notes on Causality
  Niels Waller, Vanderbilt University, Nashville
  
  
• Causal and Statistical Reasoning
  Richard Scheines et al., Philosophy Department, Carnegie Mellon University, Pittsburgh
  
  
• The TETRAD Project: Causal Models and Statistical Data
  Richard Scheines et al., Philosophy Department, Carnegie Mellon University, Pittsburgh
  
  
• David A. Freedman (1938–2008)
  University of Berkeley, California, Department of Statistics
  
  
• Publikationen: Forschungsgebiet Theorie kausaler stochastischer Abhängigkeit
  Rolf Steyer's Lehrstuhl für Methodenlehere und Evaluationsforschung, Friedrich-Schiller-Universität, Jena.
  
  
• Judea Pearl
  University of California, Computer Science Department, Los Angeles
  
  
• Statistical Modeling, Causal Inference, and Social Science
  A weblog for research in statistical modeling and applications, expecially in social sciecne; Sam Cook, University of Columbia, Department of Statistics, New York
  
  

• The R Project for Statistical Computing
  
  
• Applied Statistics Algorithms
  Carnegie Mellon University, Department of Statistics, Pittsburgh
  
  
• StatLib at Carnegie Mellon University
  Carnegie Mellon University, Department of Statistics, Pittsburgh