Are you interested in working with a dynamic team of researchers? Do you have the ambition to contribute to scientific progress? Then a PhD position at the department of Methodology and Statistics of Utrecht University might be just the right job for you. You will work on the project “Bayesian Evidence Synthesis for informative hypotheses: Aggregating evidence from conceptual replications”, which is funded by the Dutch Research Council (Open Competition scheme).

The proposed research investigates a novel tool for aggregating evidence from studies that investigate a common theory but are too diverse to aggregate with traditional approaches (e.g., meta-analysis). When studies vary considerably with regard to research design, operationalisations of key variables or statistical models used, the parameter estimates or effect sizes may no longer be comparable across studies. This can typically be the case in conceptual replications and complicates the quantification of the evidence for a scientific claim over multiple conceptual replications studies.

A solution is found in an approach that aggregates at the level of hypotheses and that is called Bayesian Evidence Synthesis (BES). In a nutshell, BES consists of three steps. First, in each study, a statistical hypothesis is formulated that reflects the overall theory, but that incorporates data characteristics and research methodology unique to that study. Then, a Bayes factor is computed which provides a measure for the amount of evidence for the hypothesis in that study. Finally, the aggregation happens at the level of the Bayes factors. The key idea is that if the study-specific hypotheses represent the same underlying (i.e., latent) effect, the Bayes factors on these hypotheses can be meaningfully combined.

Previous work has shown that the BES aggregation approach is easy to apply. However, more work is needed on the interpretation of the resulting numbers. Recent work showed that BES generally performs well, but that it is different from data pooling methods like Bayesian sequential updating and meta-analysis. Data pooling methods provide the support for a hypothesis of interest taking all studies together and thus increases the total sample size and statistical power to find support for the true hypothesis. In BES, on the other hand, the evidence in each study is determined first and then the support levels are combined over studies. In a way, it provides the extent to which hypotheses of interest are supported in each study.

Important questions that will be investigated in this project concern the impact of (potentially different) sample sizes of individual studies, and specifically how to deal with underpowered studies in the context of BES. Also, the impact of (potentially different) complexities of the hypotheses of the individual studies is of particular interest. Finally, heterogeneity of the true population effects does impact BES results and thus requires guidelines to be formulated for the implementation of BES. The main objective of this project is therefore to further develop and investigate BES, and to disseminate resulting guidelines for its use. It will include simulation-based research and implementation(s) of BES in practice in collaboration with research in psychology.

If you would like to receive the full project description, send an email to k.vankats@uu.nl.

The PhD candidate will be supervised by dr. Duco Veen and Prof. Irene Klugkist, both experts in the field of Bayesian methodology in general, and Evidence synthesis and Bayesian informative hypothesis testing specifically.

The responsibilities of the PhD candidate are:

• conducting the research (literature research/review, conducting simulations in R, presenting the results, preparing and storing R packages for sharing);
• writing international scientific publications and a dissertation that combines the theoretical, statistical and applied aspects of the project;
• giving presentations at (inter)national scientific conferences;
• active participation in the research team of the UU department of Methodology and Statistics (M&S);
• collaborating with researchers from psychology to synthesise their data as a proof of concept (see the proposal for more details);
• knowledge utilisation: collaborating and sharing findings with a broader audience (see proposal for more details);
• following courses/trainings (e.g., statistical courses)

Your work will also include teaching tasks and statistical consultancy. The amount of time spent on teaching and consultation will, in total, be between 10% (default minimum) and 20% (contract will be extended accordingly to have the standard total research time to deliver the PhD thesis).

We are looking for an enthusiastic colleague (m/f/x) who meets the requirements below:

• You have (completed or almost completed) a Master’s degree in the field of Methodology and Statistics.
• Preferably, you are familiar with R, conducting a simulation study, and Bayesian methods/hypothesis testing.
• You have well-developed analytical skills.
• You are a motivated and collaborative team member. You're communicative and open for collaboration across scientific fields. You are able to work independently and have excellent verbal and written communication skills in English.

You will be offered a temporary position (0.8 - 1.0 FTE), initially for one year with an extension to a total of 4-5 years (depending on total fte and amount of teaching), upon a successful assessment in the first year, and with the specific intent that it results in a doctorate within this period. The gross salary ranges between € 2,541,- in the first year and € 3,247,- in the fourth year of employment (scale P according to the Collective Labour Agreement Dutch Universities) per month for a full-time employment. Salaries are supplemented with a holiday bonus of 8% and a year-end bonus of 8.3% per year.

In addition, Utrecht University offers excellent secondary conditions, including an attractive retirement scheme, professional development, (partly paid) parental leave, sports and flexible employment conditions (multiple choice model). For more information, please visit working at Utrecht University.

You will work in a collaborative, social and dedicated team. We will guide you in your research and teaching tasks, which will help you develop your academic career.

A better future for everyone. This ambition motivates our scientists in executing their leading research and inspiring teaching. At Utrecht University, the various disciplines collaborate intensively towards major strategic themes. Our focus is on Dynamics of Youth, Institutions for Open Societies, Life Sciences and Pathways to Sustainability. Sharing science, shaping tomorrow.

The Faculty of Social and Behavioural Sciences is one of the leading faculties in Europe providing research and academic teaching in cultural anthropology, educational sciences, interdisciplinary social science, pedagogical sciences, psychology, and sociology. Almost 7,000 students are enrolled in a broad range of undergraduate and graduate programmes. The Faculty of Social and Behavioural Sciences has some 1,100 faculty and staff members, all providing their individual contribution to the training and education of young talent and to the research into and finding solutions for scientific and societal issues.

The faculty strives for diversity among its employees and students and is committed to creating a safe and inclusive environment for everyone, as can be read in Utrecht University's Equality, Diversity and Inclusion policy.

The faculty attaches great importance to the fact that its employees can be widely deployed in the university organisation, now and in the future, to further professionalise the support of education and research. To encourage this, every employee is given the time and facilities – for example in the form of training – at some point in their career to participate in projects or work in other departments. Characteristics that the faculty considers important are involvement, the ability to collaborate and flexibility.

The faculty is located at Utrecht Science Park near the historical city centre of Utrecht.