Course in Evidence for Public Health Responses: Statistical Methods in Epidemiology
Amsterdam, Netherlands
Course
DURATION
3 weeks
LANGUAGES
English
PACE
Full time
APPLICATION DEADLINE
22 Jan 2027
EARLIEST START DATE
22 Mar 2027
TUITION FEES
EUR 1,995 *
STUDY FORMAT
On-Campus
* early bird fee if paid 3 months before start of the course
Key Summary
About: KIT Institute's course covers statistical methods for evidence-based public health. You'll learn to plan epidemiological field surveys: formulate research questions, write protocols and field manuals, and prepare analysis plans. You’ll cover sample size calculations and sampling methods to ensure precision, representativeness; analyze complex survey data using clustering and weighting; build linear and logistic regression models in R; and construct applied multivariate models, selecting and operationalizing variables with conceptual frameworks. Keywords: epidemiology, biostatistics, survey design, sampling, regression, R.
Career Outcomes: Leads to roles as epidemiologist, biostatistician, public health analyst, surveillance officer, data scientist, M&E specialist, policy advisor, or research scientist.
This course covers a comprehensive array of statistical methods essential for evidence-based public health responses. You will begin by learning the practical aspects of planning epidemiological field surveys, including the formulation of research questions, development of a protocol, field manuals, and the formulation of data analysis plans.
Next you will delve into statistical components, including sample size calculations and various sampling methods to ensure the statistical precision and representativeness of research findings.
The course will then explore advanced techniques for analysing complex survey data, such as clustering and weighting, to extract meaningful insights.
Moreover, you will learn to build linear and logistic regression models in R -statistical programme language. And you will learn to construct epidemiologically sound multivariate models operationalizing and selecting variables based on relevant conceptual frameworks.
The following subjects are covered during the course:
- Planning epidemiological field survey
- Research questions, protocol development, data analysis plan, field manual
- Sample size calculations and sampling methods
- Analysis of complex survey data: clustering and weighting
- Linear and logistic regression in R and building multivariate models
At the end of this course participants will be able to:
- Formulate research questions for epidemiological field surveys based on stakeholder information needs, develop protocols, data analysis plans, and field manuals to ensure comprehensive planning and execution
- Calculate appropriate sample sizes and select sampling methods to ensure the statistical precision and representativeness of survey data in public health research
- Analyse complex survey data using relevant statistical techniques such as clustering and weighting
- Apply linear and logistic regression techniques in R to conduct simple and multiple regression analyses, and construct multivariate models based on epidemiologically sound conceptual frameworks
Engagement in this course will involve a combination of interactive lectures, practical workshops, case studies, and group discussions. Participants will apply theoretical knowledge through hands-on exercises in R based real-world datasets and research questions. Feedback and guidance from experienced instructors will facilitate an immersive learning experience, fostering critical thinking and problem-solving abilities essential for driving evidence-based public health responses
Assessment:
For participants who wish to receive a certificate of completion of the course, including the ECTS credits, the assessment is required.
If you do not wish to do the assessment, you can receive a certificate of attendance of the course.