Students will be made aware of the methodological, ethical and regulatory issues of research projects that involve humans. After completing the course, students will know basic and advanced statistical methods, their background, assumptions and limitations, as well as the scientific EMA guidelines for the conduct and the analysis of clinical studies.

Students will be able to plan the design, sample size, conduct, and analysis of their research projects and will be able to justify their research plans in an ethics application. Students will identify which methods are appropriate in the different types of research problems, write down the details of the analysis in a statistical analysis plan and perform specific analyses using statistical software.

Students will be able to choose which method is related to specific questions in psychological research, translate these questions to a prioritized set of statistical hypotheses, plan the conduct of the study and the analysis and interpretation of the results of their studies. Students will be able to perform simple statistical analyses using different types of software including SPSS, SAS and R. Students will know how to handle missing data, violations of the study protocol and issues of multiple testing.

The course will start with an introduction to basic statistical methods for comparison of two treatment groups (Student’s t test, chi-square test, Mann-Whitney test). Based on these simple methods, we will acquire an overview on different data types and research designs, software solutions, and ethical (data protection, informed consent, equipoise principle) and practical issues related to the conduct of empirical studies in humans (intention to treat principle, handling of protocol violations, missing data, multiple testing, randomization techniques). Based on these considerations, the participants will write a study protocol for their own research project and send it to the institute’s ethics committee for approval.

In the second part, we will treat more advanced methods (e.g., regression techniques for categorical, ordinal, and interval data, event counts, event times, basic issues in measurement and psychometrics, multilevel models, structural equation models, interim analyses). The choice of the topics will depend on the specific needs of the participants.

Tuesday 9-16, Seminarrummet i Bygning 30