May Intensive Workshop: Missing Data and Applied Solutions

Date: 
Wednesday, May 23, 2012 - 09:00 to Thursday, May 24, 2012 - 17:00
Location: 
B&E, 148, 105

 Missing Data and Applied Solutions (May 23-24, 2012) 

  • Instructor: Fred Boehmke, Political Science, University of Iowa
  • Where: B&E, 148, 105
  • When: May 23 & 24, 9 am  to 4:30 pm, with a break for lunch (12 pm to 12:45).
  • Who is eligible? Graduate students and faculty at the University of Kentucky can enroll for free.
  • Reading list (see Allison Sage monograph for the best single source), Poster
  • Complete Workshop Materials (This is a zip file containing all relevant files for the Missing Data portion of the workshop--i.e., data sets, Stata do files, outlines of the exercises, lecture slides, and reading list. All the Stata do files have been annotated and edited by QIPSR to make the exercises more accessible for individuals with a working knowledge of Stata. For an overview of all the missing data exercises and relevant files, see "List of Exercise Topics...."  (Note: the zip file does not include files related to the Selection topics.)   

Description: (details here)

  • The two-day workshop will discuss different forms of missing data, attendant problems and various solutions.  The presentation will include lectures in the morning session (in B&E 148) and computer lab sessions in the afternoon (in B&E 105).  The basic principles of missing data will be covered, as well as how to address the problem theoretically and practically using various software solutions. Emphasis will be on acquiring a practical understanding for applied researchers.
  • Participants should have a basic knowledge of data manipulation and analysis in Stata (or similar software), including generating variables and running common regression models for continuous and binary data.
  • Supported by QIPSR, Statistics, Agricultural Economics, and the Center for Poverty Research, as well as Sociology, Political Science and the College of Arts & Sciences. 

 

Materials: 
Event type: 
Statistical Workshop
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