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PPG 2010: Panel Data Methods for Public Policy Analysis

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PPGPortal > Home > Illustrative Courses > Toronto (SPPG) > PPG 2010: Panel Data Methods for Public Policy Analysis


PPG 2010  - 
Panel Data Methods for Public Policy Analysis 

University of Toronto 



The course provides a rigorous introduction to statistical methods for the analysis of panel data with specific application to the major Canadian longitudinal data sets. This course is offered in collaboration with the Toronto RDC. The RDC provides secure access to Canada's preeminent panel data sets for public policy analysis as well as variety of other Statistics Canada data. The course will take place within RDC providing students hands on experience with these important sources of information on public issues. The RDC offers both lecture space and a computer lab for tutorials. While the specific goal of this course is to introduce students to empirical methods for the analysis of longitudinal data, an important by product is their exposure to the RDC data. These data are increasingly "the basis" for new survey based research in health, education, economics and other social sciences in Canada. Instruction includes a combination of lectures and tutorials. In tutorials, students will complete series of problem sets that provide an introduction to the RDC panel data sets and practice in their analysis. The statistical methods reviewed will be drawn from a variety of disciplines to promote the inter-disciplinary study of public policy. Certain topics of particular relevance to the RDC panel data (e.g., cluster sampling, bootstrapping) will also be covered. The course is intended for a) students from the School of Public Policy and Governance, b) students from departments, schools and faculties where small numbers preclude a similar course being offered, or that desire instruction in the use of data housed in the Toronto Region Statistics Canada Research Data Centre (RDC).

Source: accessed 4 January 2014.

Instructor: Olesya Falenchuk

Commentary by the Atlas editors: The class titles in the Syllabus suggest a number of the potential topics to be developed for the Atlas:

  • Data management and manipulation 
  • Descriptive Statistics: Overview of Core RDC Datasets
  • Principles of Statistical Modeling
  • Multiple Regression as an Example of Statistical Modeling
  • Multilevel Modeling of Panel Data: Basic Principles
  • Modeling Discontinuous Change
  • Latent Growth Modeling
  • Modeling Panel Data with Binary and Ordinal Outcome Variables
  • Modeling Panel Data with Count Outcome Variable
  • Survival Analysis

Page created by: Ian Clark on 30 January 2014. The content presented on this page, except in the Commentary, is drawn directly from the source(s) cited above, and consists of direct quotations or close paraphrases.


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 Courseware Library

PPG2010H - Falenchuk_RDC_2014.pdfPPG2010H - Falenchuk_RDC_2014Ian Clark

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School of Public Policy and Governance