Generalized linear models
The course introduces models that are various extensions of the linear regression model. These extensions offer greater flexibility for data analysis by allowing other common types of data to be analyzed. The course covers modeling and analysis of binary data, categorical data, proportions, count data, contingency table data, and longitudinal data.
The course provides an overview of several models with a focus on practical applications: being able to select appropriate models based on data, estimate models through programming in R, and interpret and critically evaluate analysis results and predictions with respect to underlying model assumptions. The definition and fundamental theory of the class of Generalized Linear Models (GLM) are covered in the course.
Information for admitted students spring 2025
Congratulations! You have been admitted at Stockholm University and we hope that you will enjoy your studies with us.
In order to ensure that your studies begin as smoothly as possible we have compiled a short checklist for the beginning of the semester.
Follow the instructions on whether you have to reply to your offer or not.
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Checklist for admitted students
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Activate your university account
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Register at your department
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Read all the information on this page
Here you will find what you need to know before your course or programme starts.
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Your seat may be withdrawn if you do not register according to the instructions provided by your department.
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Welcome activities
Stockholm University organises a series of welcome activities that stretch over a few weeks at the beginning of each semester. The programme is voluntary (attendance is optional) and includes Arrival Service at the airport and an Orientation Day, see more details about these events below.
Your department may also organise activities for welcoming international students. More information will be provided by your specific department.
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For new international students
The course introduces models that are various extensions of the linear regression model. These extensions offer greater flexibility for data analysis by allowing other common types of data to be analyzed. The course covers modeling and analysis of binary data, categorical data, proportions, count data, contingency table data, and longitudinal data.
The course provides an overview of several models with a focus on practical applications: being able to select appropriate models based on data, estimate models through programming in R, and interpret and critically evaluate analysis results and predictions with respect to underlying model assumptions. The definition and fundamental theory of the class of Generalized Linear Models (GLM) are covered in the course.
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Course structure
The course is given at day time, full time.
Teaching format
The teaching consists of lectures, exercises, and computer exercises.
Assessment
The course is examined through an individual written exam and a group assignment.
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Schedule
The schedule will be available no later than one month before the start of the course. We do not recommend print-outs as changes can occur. At the start of the course, your department will advise where you can find your schedule during the course. -
Course literature
Note that the course literature can be changed up to two months before the start of the course.
