Advanced Statistical Topics in Health Research
Provider: Faculty of Health and Medical Sciences

Activity no.: 3330-17-00-00 
Enrollment deadline: 06/10/2017
Date and time06.11.2017, at: 10:00 - 09.11.2017, at: 17:00
Regular seats29
Course fee3,720.00 kr.
LecturersClaus Thorn Ekstrøm
ECTS credits2.80
Contact personSusanne Kragskov Laupstad    E-mail address: skl@sund.ku.dk
Enrolment Handling/Course OrganiserPhD administration     E-mail address: phdkursus@sund.ku.dk

Aim and content
This is a generic course. This means that the course is reserved for PhD students at the Graduate School of Health and Medical Sciences at UCPH. Anyone can apply for the course, but if you are not enroled as a PhD student at the Graduate School, you will be placed on the waiting list until enrolment deadline. After the enrolment deadline, available seats will be allocated to applicants on the waiting list.

The course is free of charge for PhD students at Danish universities (except Copenhagen Business School). All other participants must pay the course fee.

Learning objectives

Many modern research projects collect data and use experimental designs that require advanced statistical methods beyond what is taught as part of the curriculum in introductory statistical courses.
This course covers some of the more general statistical models and methods suitable for analyzing more complex data and designs encountered in health research such as methods for high-dimensional data, classification, imputation, and dimension reduction.

The course will contain equal parts theory and applications and consists of four full days of teaching and computer lab exercises. It is the intention that the participants will have a thorough understanding of the statistical methods presented and are able to apply them in practice after having followed the course. This course is aimed at health researchers with previous knowledge of statistics and the computer language R who need of an overview about appropriate analytical methods and discussions with statisticians to be able to solve their problem.

A student who has met the objectives of the course will be able to:

a. Analyze data using the methods presented and be able to draw valid conclusions based on the results obtained.
b. Understand the advantages/disadvantages of the methods presented and be able to discuss potential pitfalls from using these methods.

Content
1. Introduction to statistical methods for high-dimensional data, linear models, regularization methods, and variable selection
- Big-p small-n problems
- Multiple testing techniques (inference correction, false discovery rates)
- Regularization methods
- The correlation vs. causation and prediction vs. hypothesis differences
- Partial least squares, principal component regression
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2. Dimension reduction methods
- Principal component analysis (PCA), PCR
- Partial least squares (PLS)
- Factor analysis and segmentation analysis

3. Bootstrapping and cross-validation
- Parametric and non-parametric bootstrap
- Cross-validation
- Randomziation testing

4. Classification and regression tress
- Classification and regression trees
- Random forests
- Variable importance

5. Imputation techniques for handling missing data
- Imputation and Rubin’s rules
- Multiple Imputation by Chained Equations

Participants
The course is tailored for Ph.D.-students in health sciences who already have taken the Ph.D.-course “Basic Statistics for Health Scientists” or have a similar knowledge about statistics, and who wish to have more knowledge about the statistical methods underlying the approaches presented in the course.

A basic knowledge of statistics and previous experience with the software program R is expected. However, little or no previous exposure to the topics covered is expected. Max. 20 participants.

Relevance to graduate programmes
The course is relevant to PhD students from the following graduate programmes at the Graduate School of Health and Medical Sciences, UCPH:

ALL GRADUATE PROGRAMMES

Language
English

Form
The course will consist of 4 full days with lectures before lunch and hands-on computer exercises after lunch each day.

Course director
Claus Thorn Ekstrøm, Professor, Section of Biostatistics, Department of Public Health, University of Copenhagen
ekstrom@sund.ku.dk

Teachers
Claus Thorn Ekstrøm, Professor, Section of Biostatistics, Department of Public Health, University of Copenhagen
Teachers from the Section of Biostatistics, UCPH

Dates
Monday 6th to Thursday 9th, November 2017, all days 10-17.

Course location
The course takes place at the Center for Health and Society (Center for Sundhed og Samfund, at the former Kommunehospital, Øster Farimagsgade 5), at the University of Copenhagen. A map of the area can be found here:(http://csc.ku.dk/bygninger_og_adresser/css/CSSOversigtskort2.pdf/ "Map of area")

Registration: Please register before 6 October 2017

Seats to PhD students from other Danish universities will be allocated on a first-come, first-served basis and according to the applicable rules.
Applications from other participants will be considered after the last day of enrolment.


Note: All applicants are asked to submit invoice details in case of no-show, late cancellation or obligation to pay the course fee (typically non-PhD students). If you are a PhD student, your participation in the course must be in agreement with your principal supervisor