Statistics for Duration Data

2024/2025

Content, progress and pedagogy of the module

Learning objectives

Knowledge

  • understand the special features of duration data (e.g. censoring, non-normality)
  • derive the likelihood function for right-censored data
  • know basic characterisations of duration data distributions such as the survival and hazard function 
  • be able to derive basic non-parametric estimates such as the Kaplan-Meier and Nelson-Aalen estimates
  • know parametric models for duration data
  • understand the assumptions underlying the Cox partial likelihood
  • derive the Cox partial likelihood 
  • know methods of model assessment for parametric models and the Cox proportional hazards model

Skills

  • be able to identify relevant type of censoring for a specific set of duration data 
  • be able to estimate and interpret survival functions or cumulative hazard functions for a specific set of duration data
  • be able to fit duration data using parametric or semi-parametric regression models
  • be able to assess the validity of a model for a specific set of duration data

Competences

  • be able to identify an appropriate duration data methodology for investigating a specified hypothesis of interest
  • be able to interpret and critically assess results of the analysis carried out using the chosen methodology
  • be able to convey the results of the analysis to a non-statistician

Type of instruction

Lectures with exercises.

Extent and expected workload

This is a 5 ECTS course module and the work load is expected to be 150 hours for the student.

Exam

Exams

Name of examStatistics for Duration Data
Type of exam
Active participation/continuous evaluation
Re-examination: Written or oral
ECTS5
Permitted aidsPlease see the semester description / module description
AssessmentPassed/Not Passed
Type of gradingInternal examination
Criteria of assessmentThe criteria of assessment are stated in the Examination Policies and Procedures

Facts about the module

Danish titleVarighedsanalyse
Module codeK-MAT1-SFDD
Module typeCourse
Duration1 semester
SemesterAutumn
ECTS5
Language of instructionDanish
Empty-place SchemeYes
Location of the lectureCampus Aalborg
Responsible for the module

Organisation

Education ownerMaster of Science (MSc) in Mathematics-Economics
Study BoardStudy Board of Mathematical Sciences
DepartmentDepartment of Mathematical Sciences
FacultyThe Faculty of Engineering and Science