HMET5140 – Non-Parametric Methods and regression alternatives

Course content

The course gives an introduction to non-parametric statistics, starting with a repetition of the difference between the mean and the median and the influence of having data with a skewed distribution. Typical examples of such data within health economics are costs of stay or the length of stay.

The course also covers simple non-parametric tests for comparing groups of observations. Methods such as the bootstrap for constructing confidence intervals in the case of skewed data is also covered. Alternative regression methods such as log-linear regression, gamma and negative binomial regression models will be discussed. Computer exercises are used throughout the course.

Learning outcome

Knowledge

• Understand the problems associated with having skewed data:
• In terms of using standard methods for hypothesis testing
• In terms of constructing confidence intervals for the mean
• Learn simple methods for transforming the data, such that standard methods may still be applied in the analysis
• Understand the concept of bootstrapping, and why this is a useful method in health economics

Skills

• Perform non-paramteric testing in software such as Stata, and interpret the output
• Being able to perform bootstrap analysis in simple situations
• Interpreting output from log-linear, gamma and negative binomial regression models

General competence

Supplemented by knowledge from introductory courses in statistics, this course will make students able to choose the correct method of analysis in a wide range of situations, and understand the importance of not violating the assumptions made in standard statistical methods.

Keywords

• The mean and median - importance of having two measures of central tendency in continuous data, in case of skewed data, tests for differences between:
• Paired samples, two independent groups of observations
• Alternatives to linear regression in case of skewed data
• Three or more independent groups of observations
• Transformation of variables
• The bootstrap - A method for constructing valid confidence intervals in the case of skewed observations.

Admission to the course

This course is only available for students at the following master programmes:

Health Economics, Policy and Management (master's two years)

European Master in Health Economics and Management (master's two years)

Students who are admitted to study programmes at UiO must each semester register which courses and exams they wish to sign up for in Studentweb.

If you are not already enrolled as a student at UiO, please see our information about admission requirements and procedures.

Recommended previous knowledge

Recommended prerequisite: HMET4101 

Teaching

Lectures and exercises

Examination

Written examination.

Examination and grading at The Faculty of Medicine.

Examination support material

A web based calculator will be available for use in Inspera.

Language of examination

For students at Eu-HEM: English

For students at HEPAM: The examination set will be given in English. Answers can be given in Norwegian, Swedish, Danish or in English.

Grading scale

Grades are awarded on a scale from A to F, where A is the best grade and F is a fail. Read more about the grading system.

Resit an examination

For Eu-HEM students:

An EU-hem student cannot present her or himself for the examination in a course more than two times. There will be held re-sits for EU-hem students who have failed an exam or who have legitimate absence (usually illness) in January and August. If you are entitled to a re-sit you must contact the student advisor via email no longer than one week after the result of the exam has been published.

More about examinations at UiO

• Use of sources and citations
• Special exam arrangements due to individual needs
• Withdrawal from an exam
• Illness at exams / postponed exams
• Explanation of grades and appeals
• Resitting an exam
• Cheating/attempted cheating

You will find further guides and resources at the web page on examinations at UiO.