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Basic statistics for health researchers - using R statistical software (Danish)
Provider: Faculty of Health and Medical Sciences

Activity no.: 3304-22-00-07 
Enrollment deadline: 05/08/2022
Date and time05.09.2022, at: 10:00 - 17.11.2022, at: 18:00
Regular seats25
Course fee5,280.00 kr.
LecturersJulie Forman
Aksel Karl Georg Jensen
ECTS credits9.00
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 a PhD student at the Graduate School, you will be placed on the waiting list until enrollment deadline. After the enrolment deadline, available seats will be allocated to the waiting list.

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


Learning objectives

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

1. interpret basic statistical information from research papers, e.g. descriptive statistics, sample size calculations, estimates of effect or association, confidence intervals, p-values, and statistical graphs.

2. understand the basic statistical analyses most commonly used in health science, including two-sample and paired t-tests, linear regression, correlation, analysis of variance (ANOVA), analysis of covariance (ANCOVA), linear models, risk difference, risk ratios, logistic regression, as well as simple applications of survival analysis and linear mixed models for repeated measurements and clustered data.

3. apply these statistical analysis to own research data using the statistical software SAS.

4. present the results of own basic statistical analyses in suitable text, tables, and figures.

5. critically assess the validity of basic statistical analyses by being aware of model assumptions and the potential biases related to e.g. small sample sizes, lack of fit, lack of power, multiple testing, confounding, and missing data.

6. have a qualified discussion with a statistical consultant e.g. when seeking advice on how to plan statistical analyses or answer the criticism raised by reviewers.


Content

Basic statistical concepts (datatypes, distributions, estimation, confidence intervals, significance tests, statistical power). Analysis of quantitative outcomes (t-tests, ANOVA, linear regression, correlation, ANCOVA, multiple linear regression, confounding, interaction). Power and sample size calculation. Binary and categorical outcomes (association in two-way tables, logistic regression). Introduction to survival analysis (Kaplan-Meier curves, log-rank test, Cox regression). Introduction to linear mixed models for repeated measurements and clustered data.


Statistical software

You are required to bring your own laptop with R statistical software installed. We expect that you have made yourself familiar with R before the course starts by completing the e-course at:

r.sund.ku.dk


In the introduction we guide you through how to install/get access to R and we teach you how to do basic data management, calculations, and plots. The introduction takes 8 +/- 5 hours. You can start working with the introduction now if you have limited time before the course starts.


If you prefer to use SAS statistical software, please enrol for the SAS-version of this course.


Participants

Ph.D.-students. In case of vacant seats, also other health researchers. Max. 25 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

Danish


Form

10 x 4 hour forum lectures with discussion and 10 x 3 hour exercise classes. Attending 8 out of the 10 exercise classes is required to pass the course. Attending the lectures is recommended but not required. Compulsory homework exercise of 20-40 hours work in groups of 2-3 students.


Course directors

Associate professor Julie Lyng Forman and Assistant professor Aksel Karl Georg Jensen


Teachers

Associate professor Julie Lyng Forman and Assistant professor Aksel Karl Georg Jensen plus external teachers.


Dates

Course 1:

- 5, 8, 12, 15, 19, 22, 26, 29 September 2022
- 3, 6, 10, 13, 24, 27, 31 October 2022
- 3, 7, 10, 14, 17 November 2022

(Mondays 10-14, Thursdays 15-18)


Course location

CSS


Registration

Please register before 5 August 2022.


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 enrollment.

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.

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