Causal Inference (Master Course, PSMM-1)

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Place and time
Second semester, period two, week 16 – 22, 2007
Wednesday's from 09.00 – 11.00 hours in room 0061 of the Muntingh Building
The first meeting is on April 18

Announcement
The guest lecturer who will teach the course will be announced in due time. The regular lecturer will be on educational leave in 2007–2008.

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 already. 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.
  
  

Evaluation and exams
Probably weekly Causal Lab assignments, and a written exam at the end of the course. The first written exam is on Monday June 11, 2007, from 09.00–11.00 hours in the Nieuwenhuis Building, Room 026 (Grote Rozenstraat 38). A second opportunity for this exam is offered on Friday June 29, 2007, from 14.00–16.00 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 15, room 221, 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
  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