Categorical Data Analysis

This course will be run during week 39, 24 september - monday, 28 september 2012 at 10:00 to frieday 28 September 12:00 (full-time course) at the School of <?xml:namespace prefix = st1 ns = "urn:schemas-microsoft-com:office:smarttags" />Business and Economics, Linnaeu University, Växjö.

For more information please contact ghazi.shukur@lnu.se

COURSE SYLLABUS<?xml:namespace prefix = o ns = "urn:schemas-microsoft-com:office:office" />

Categorical Data Analysis (CDA)

CDA refers to statistical techniques concerned with analyses where the response variables are categorical regardless of whether the explanatory variables are continuous or categorical. Categorical variables can have two types of scales, nominal and ordinal. It is common in all behavioral  sciences.

Course Code                      3FNA015

Date of Decision                

Decision-making Body       Fakultetsnämnden för ekonomi och design

Valid from                          2012-06-01

Language of instruction     English

Subject                                Economics/Statistics

ECTS credits                      7.5

Level                                   PhD-level

Type of course                   Included in the PhD-programme in economics and Statistics .

Prerequisites                       15 ECTS credits in Statistics and an intermediate course in

                                            Econometrics or quantitative methods is recommended. It is also

                                            assumed that all participants have a basic knowledge of Linear and

                                            Generalized Linear methods (GLM).

Expected learning

outcomes                              The aim of the course is to give the students basic knowledge in

                                             categorical data analysis (CDA) from both theoretical as well as

                                             practical perspective. The course is designed to help doctoral

                                             students in their empirical analysis with CDA. The course will

                                             provide an up-to-date overview on the most commonly used

                                             models within this area. The course will also provide tools for

                                             using the statistical packages R and how to apply this in the thesis

                                             work of the doctoral students.  

Course contents                

• Introduction to categorical data.
• Why using CDA Modelling
• Single, double and multiple variable associate testing
• Generalized Linear Multilevel modelling
• Prediction from Generalized linear Model
• Bayesian CDA  model
• R free software
• R code to run different CDA modelling
• Using R to Data from Participants.

Teaching methods              Lectures, seminars and computer assignments

Course literature

Categorical Data Analysis, Alan Agresti, 2002 (2nd ed) or 2012 (3d ed) Wiley

Assessment methods          Presentations of papers.

Type of grades                   Pass/not pass

Study certificate                 Student who has passed the course will get a study certificate.