Dr. Rebecca Kuiper

Sjoerd Groenmangebouw
Padualaan 14
3584 CH Utrecht

Dr. Rebecca Kuiper

Associate Professor
Methodology and Statistics

Welcome to my UU-webpage.

I am an associate professor at the Department of Methods and Statistics at University Utrecht. I am passionate about doing research in the field of (bio)statistics & psychometrics and behavioural & social sciences, since there are a lot of statistical challenges I like to tackle (which in the end also contribute to society). 


My specializations are

I teach the first three subjects in the postgraduate course "Beyond null hypothesis testing". Together with a PhD student, I developed the information criterion GORICA (Altinisik et al., 2021). I have applied GORICA to

   - structural equation models (SEM models) in Kuiper (2021)

      [I teach about this in this lavaan e-learning postdoctoral course]

   - 'CTmeta-analyzed' parameters (Kuiper, 2021), and

      [I teach about this in this dynamical modelling e-learning postdoctoral course]

   - meta-analysis (Kuiper, 2022).

Furthermore, I combine the fourth subjects, lagged-effects models, with my theory-based model selection expertise, for which I received a VENI-grant (2016-2020). In Kuiper and Ryan (2018), Oisín Ryan and I address both the continous-time (CT) and discrete-time (CLPM/VAR(1)) lagged-effects model and we give insight in when you should definitely use a CT-model and when a discrite-time model would suffice. We also developed CTmeta: meta-analysis for the time-interval dependent lagged parameters of these lagged-effects models (Kuiper and Ryan, 2020). Additionally, I showed how the information criterion GORICA can be applied to order restrictions on the resulting overall estimates (Kuiper, 2021). I teach about this in the postgraduate course "Modeling the dynamics of intensive longitudinal data".


Because of the calls for replication and the unexploited wealth of information in existing and future conceptual replications (more specifically, studies using diverse designs) and the recent developments in model selection (e.g. Vanbrabant et al., 2020; Kuiper et al., 2020; Altinisik et al., 2021), my current research focus is to connect my knowledge of evidence synthesis (Kuiper et al., 2013; Kuiper and Ryan, 2020; Kuiper, 2021; Kuiper, 2022) with my expertise in model selection. The developed and to-be-developed methods will harness the combined potential of heterogeneous and homogeneous studies: which increases the power, robustness, and generalizability of findings; and it will render previously inaccessible insights into societal problems. In 2022, I was awarded NWO Aspasia funding to work on this (and to become an associate professor). My team and I will develop methods such that evidence for theory-based, informative hypotheses can be aggregated, including evidence from studies with heterogenous study-designs like in conceptual replications. The current and preliminary findings are addressed in the postgraduate course "Beyond null hypothesis testing".


I made software and interactive web applications (Shiny apps). These are all free of use (in turn for referring to my work in case you use it for a publication):

  • Under the tab Software you can find the free software I made with respect to hypothesis testing and model selection (both stand-alone software and R functions). In case you want to know more about the AIC-type criterion GORIC, please click here.
  • Under the tab Websites / Shiny apps you can find the interactive web apps and R functions I have made for the first-order discrete-time model (i.e., VAR(1)) and continuous-time model (CTM).

Have fun with them and do not hesitate to contact me in case of questions.


For more research output: