I am an associate professor (i.e., reseracher and teacher) at the Department of Methodology & Statistics at the Utrecht University. 

My first line of research is an independent continuation of my PhD-projects. In this line, I developed (together with PhD-students) hypothesis-evaluation techniques called GORIC and GORICA: information criteria that can evaluate theory-based hypotheses. This led to several first- and last-author publications in journals such as Journal of Statistical Software, Biometrika, Psychological Methods, and Structural Equation Modelling, and to open-source software (R packages, (shiny) web applications, and stand-alone software) with accompanying tutorials/vignettes. Internationally and nationally, I am a renowned expert in the field of evaluating theory-based hypotheses using information criteria, as can be seen from my CV. For example, I have been invited to give a state-of-the-art presentation and workshop at the EAM conference and to give presentations at the national university medical center VUMC and for universities in Hannover. The GORIC-research is not only continued via my network, but also extended with PhD-students. 

In case you are interested in applying the GORIC to evaluate informative hypotheses (also in the context of replicating studies), I refer you to the following postgraduate course (in the summer): "Open science hypothesis testing". I can also give such a workshop on request.

After my PhD, I started an independent second research line in the field of modeling lagged relationships. Utrecht University awarded me research time, using NWO Aspasia funding, for working in this area. In 2016, I received a Veni grant, in which I brought these two research topics together such that researchers can model individually-varying cross-lagged relationships and evaluate their hypotheses regarding these relationships. I am participating in the Dutch-Flemish network group regarding Time Series and Network Dynamics (DynaNet), consisting of psychometricians, statisticians and substantive researchers. My publications are in journals like Psychological Methods and Structural Equation Modelling. Also on this topic, I am considered an expert: I receive invitations to presentations and workshops and to supervise PhD-students who have their own funding. With my Veni grant, I brought/bring both my research topics together such that researchers can model individually-varying cross-lagged relationships (with a multivariate multilevel continuous-time model) and evaluate their hypotheses regarding these relationships.

Kuiper and Ryan (2018) discuss both the continous-time (CT) and discrete-time (CLPM/VAR(1)) model and give insight and when you should definitely use a CT-model and when a discrite-time model would suffice. Kuiper and Ryan (2020) developed meta-analysis for the time-interval dependent lagged parameters of these lagged-effects models and I (Kuiper, 2021) show how the information criterion GORICA can be applied to order restrictions on the resulting overall estimates. This is part of the following postgraduate course (in the summer): "Modeling the dynamics of intensive longitudinal data".

Due to the calls for replications, I connected my two research lines with meta-analysis: I developed continuous-time meta-analysis for cross-lagged models to correct for the time-interval dependency of the lagged-estimates (CTmeta; Kuiper and Ryan, 2020; Kuiper, 2020); and applied the GORICA to the resulting overall lagged-estimates (Kuiper, 2021). I notice(d) that a wealth of valuable information remains unexploited. To prevent this from being research waste and thus a waste of money, I will (further) develop evidence synthesis: the aggregation of support for a central hypothesis. I also extended the use of the GORIC (e.g., Vanbrabant et al., 2020) and developed GORICA (Kuiper et al., 2020; Altinisik et al., accepted), which aids the development of evidence synthesis. Thus, now, it is time for the next step: Use my model selection expertise in aggregating evidence to (futher) develop evidence synthesis methods, using GORIC(A) and BMS. This method 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. 

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, also those 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:

• Under the tab CV you can download my CV and my publications can also be found under the tab Research output.
• Here you can find the post-prints of my first-author publications.
• Here (on my GitHub page), you can find html tutorial files with R code for the GORIC and GORICA (when having one or more studies). 
• Here (on my GitHub page), you can also find a (html and pdf) vignette/tutorial for CTmeta ("Introduction to CTmeta...").
• I also share R scripts and more on my GitHub page.