1. What is Statistical Modeling?

Statistical modeling is the foundation for turning complex questions into meaningful, data-driven answers. Whether you’re analyzing longitudinal data, running an experiment, or exploring latent constructs, the right model helps you uncover patterns, quantify uncertainty, and test theoretical frameworks.

With years of experience in academic and applied research, I offer modeling support that balances methodological rigor with practical impact — always tailored to your data, research questions, and audience.

2. What I Offer

I help researchers and organizations select, implement, and interpret statistical models with precision and clarity. My goal is to support you in making informed decisions, producing robust results, and navigating statistical challenges with confidence.

Areas of expertise include:

  • Structural Equation Modeling (SEM)
  • Multilevel and mixed-effects models
  • Bayesian models (e.g., using stan)
  • Repeated measures and longitudinal models
  • Causal inference (mediation, moderation, propensity scores)
  • Simulation-based model evaluation
  • Time series and dynamic models
  • Regularized regression and model selection

Services include:

  • Designing and implementing statistical models
  • Reviewing or refining existing analyses
  • Providing clear interpretation of complex outputs
  • Simulating data to assess power, bias, or estimation quality
  • Writing methods/results sections for publications
  • Coding in R, Python, or stan with reproducible workflows

3. Consulting Packages

All packages can be tailored to your specific needs and timeline. Whether you need a one-off consultation or ongoing collaboration, I’m happy to create a custom solution.

Model Check-In

A focused consultation session to:

  • Review your current model or plan
  • Troubleshoot issues or refine assumptions
  • Suggest improvements or alternative approaches

Best for when you’re stuck mid-analysis or need expert validation.

Full Project Support

End-to-end modeling support for a specific project or dataset:

  • Discussion of goals and hypotheses
  • Model design and implementation
  • Iterative feedback and refinement
  • Optional: support with interpretation and scientific writing

Perfect for academic papers, grant applications, or applied research projects.

Ongoing Collaboration

A retainer-style partnership for continued support:

  • Regular access to statistical modeling expertise
  • Ideal for labs, research groups, or data teams
  • Includes feedback on multiple projects over time

Best for teams who need recurring input on modeling decisions or want to streamline reproducible workflows.

4. Who This Is For

  • Researchers working with experimental, longitudinal, or hierarchical data
  • PhD candidates needing modeling support for dissertations or publications
  • Applied data scientists tackling complex health, social, or behavioral data
  • Organizations seeking robust and defensible models for decision-making

5. Why Work With Me?

I’m an Assistant Professor of Methodology & Statistics at Maastricht University with a PhD in Quantitative Psychology and a strong background in applied data analysis, Bayesian modeling, and statistical software development. I’ve authored peer-reviewed papers on SEM, mediation, and longitudinal models, and regularly support research teams in health, behavioral science, and social data contexts.

I combine academic rigor with hands-on expertise to help you build models that are both statistically sound and practically useful.

6. Ready to Get Started?

Let’s talk about your project and how I can help. I’m happy to tailor a custom package based on your needs.