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Epidemiology, Biostatistics and Prevention Institute

Clinical Research Methods

We are a team of researchers at the Department of Biostatistics with backgrounds in statistics, biology, psychology, movement sciences, mathematics, and informatics - all with profound expertise in clinical research. We support researchers from UZH Faculty of Medicine during all phases of the research cycle, from study design to data analysis, interpretation and publication of results. We recommend that you contact us during the study design phase. We aim to maintain the highest standards regarding methodology, reproducibility, and medical research quality generally.

 

wordcloud biostatistics

We have expertise in

  • Study design, sample size calculation, advanced trial design like adaptive design (Study Design Board)
  • Statistical analysis plans
  • Advanced methods for statistical data analysis and graphics (including methods to avoid bias, regression, matching, trees, interpretation of results)
  • Meta-analysis (including advice for systematic literature searches, meta-analysis of diagnostic studies, meta-analysis of observational data, meta-regression, network meta-analysis)
  • Publication of high quality medical research papers following the EQUATOR guidelines

 

Please read this page carefully and check out how we can support you.

Registration

For Clinical Researchers at USZ / UZH

Please contact us early in your planned research project, ideally before submitting your protocol for ethics approval and data collection. We will discuss study design issues, required number of patients as well as suitable analysis strategies with you.

We offer joint meetings with representatives of the Clinical Trials Center to discuss different aspects of your planned research project simultaneously. For projects resulting in contractual collaboration, we prepare a cost estimate. We charge 120 CHF per hour for meetings and contractual collaborations. You will receive a reproducible report using the statistical programming language R and dynamic reporting, including all relevant aspects of our work.

For Students of the Medical Faculty at UZH

If you are writing your Master thesis or if you are working on a medical dissertation project, we offer one hour of statistical advice. This hour is free of charge. For these projects, we cannot offer contractual collaboration. This does not apply for PhD students.

If you are interested in learning more about statistical analysis of medical data or related topics using the programming language R, please check out our new R courses. You may also be interested in coming to our R Code Clinic, Thursdays, 16.15-17.15 at HRS F28. Please send us an email in advance.

Statistical Programming

We use the statistical programming language R for all analyses. R is a free, open-source software, that produces high-quality, reproducible reports when used in conjunction with dynamic reporting tools such as Markdown, knitr, or Sweave. If you conducted your analyses with any other statistical software, we will discuss the findings with you, but we cannot take the responsibility for correctness.

Grant Applications

If you are planning to apply for a grant, please contact us early. We act as project partners and take responsibility for suitable study design and power analysis. If the grant is awarded, we will write up statistical analysis plans, and carry out data analysis including interpretation of the findings and figures during the publication process. If you are interested, we offer meetings together with representatives of the Clinical Trials Center at USZ.

Authorship

We follow the International Committee of Medical Journal Editors (ICMJE) guidelines for authorship in medical publications. In projects with contractual collaboration, preparations for publication including revisions of the manuscript will not be charged.

Please have a look at our view on authorship (PDF, 155 KB).

External Researchers

If you are a researcher outside of UZH Faculty of Medicine, please contact  Eveline Bielser (administration) before registration.

Other options to collaborate with us

Funding of a part-time position of a biostatistician to work in your clinic

Design of experiments, analysis and interpretation of clinical data is complex, and standards are high in medical research. Graduates of our master program Biostatistics have a sound methodological background and strong interest in biomedical applications. A long-term collaboration of a biostatistician with your group of clinical scientists improves research output and quality.

Please contact us, if you are interested in hiring a part-time biostatistician.

 

Statistical co-supervision of medical dissertation projects at UZH MeF

Some medical dissertation projects require more intense statistical support. These projects can be co-supervised by members of our team using the programming language R. Participation in an R course beforehand is a prerequisite. We will offer this to students and their supervisors.

Dissertationsvereinbarung (PDF, 21 KB)

 

Data analysis by students of our master program Biostatistics

Students of the master program Biostatistics need to get experience in real-world data analysis and statistical consulting. In the Statistical Consulting Module (STA490) of our master program Biostatistics, each student is working on a clinical research project under the supervision of an experienced staff member of Dept. of Biostatistics or Dept. of Epidemiology. Detailed information can be found here. If you have an interesting research question formulated and a data set prepared, this could be an option for you.

 

Scientific cooperation

Some medical research questions may also be relevant to methodological research and may be suitable for scientific cooperation. The main goal of such a cooperation is to make scientific advances in both the methodological and medical fields, resulting in publications in both biostatistics/methodological and medical journals. In these projects, our team members would be first or last author. Pre-requisites for such scientific cooperation include joint grant applications, previous published papers as co-authors, or corresponding research activities or interests.

Weiterführende Informationen

Registration for Consulting

Click here for Registration. You will be contacted by a member of our team within 2-3 days to set up an appointment. Please contact us in a timely manner.

 

R Courses for Medical Research

The course covers basics of programming and data formats in R, and the essential steps of a data analysis including data manipulation, descriptive statistics, statistical tests and graphical representations. The course is taylored to medical research, and is funded by the Medical Faculty. Basic statistics knowledge from bachelor and master program Medicine is a prerequisite. Courses are limited to 20 participants.

Next course:

Wednesday, April 3, 2024 and Friday, April 5, 2024 (13:30 - 17:00, in person)

For registration please click here.

For more information about the course, please contact Monika Hebeisen.

Get R_eady R Courses

We offer three courses to increase digital skills with funding by the DISK4U initiative. The courses are transdisciplinary, and they are open to students at Master and PhD level across faculties.

Introduction to Data Analysis for Empirical Research

Dynamic Reporting & Reproducibility in Research

Prognostic & Prediction Modelling in Research

For more information about the courses, please contact Monika Hebeisen.

R Code Clinic

We hold regular R Code Clinic sessions to provide help for medical students or clinical researchers with their own R code. Sessions take place Thursdays, 16.15-17.15. If you are planning to join a session please send an email to  Monika Hebeisen.

Statistical Lab Pitches

Statistical lab pitches are workshops, held by members of the biostatistics consulting team. These cover specific methodological topics that are tailored to the needs and questions of your UZH institute. Examples of such talks can be found here. Please contact  Manja Deforth if you are interested.

LIGHTS database for methods guidance

The Library of Guidance for Health Scientists (LIGHTS) provides methods guidance articles for all steps in a research project including conceptual planning, study design, feasibility studies, stakeholder involvement, quantitative and qualitative analyses, subgroup and sensitivity analyses, tables and figures, reporting, and quality assessment. The developers welcome any comments and suggestions via email.