Statistical Consulting
“All models are wrong, but some are useful.”
Statistics is central to the process of research. From planning a study to the interpretation of results, Statistics inform researchers about what can be learned from data. Regardless of whether the study is observational or experimental, Statistics offers scholars a wide variety of methods to leverage an appropriate translation between data and reality.
EXPERIENCE
I have consulted for the following:
Department of Psychology, New York University, New York, US
Sciences Po, CEVIPOF, Paris, France
Department of Psychology, Lund University, Lund, Sweden
Unité de Psychologie de la Sénescence (UPsySen), Faculté de Psychologie et des Sciences de l'Education, Université de Liège, Liège, Belgium
Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, the Netherlands
Cologne's Center for Comparative Politics, Cologne University, Cologne
EDUCATION
I have been formally educated in Statistics at Leiden University (M.Sc.) in the Netherlands. I am experienced in handling multilevel and multivariate analysis, including dealing with linear (and non-linear) mixed models. Recently, I have specialized in Latent Variable Models and Psychometrics. Specifically in Item Response Theory, Latent Class Analysis and Structural Equation Models (SEM), as well as their accompanying techniques: Path Analysis and Latent Growth Models, and Exploratory and Confirmatory Factor Analysis (CFA).
expertise
I offer statistical advice on selecting appropriate experimental designs, calculating power and sample sizes, and data analysis. Moreover, I provide intuitive interpretation of results tailored to the client's level of expertise, as well as provide state of the art graphical representations of the research findings.
In the past, I have worked on issues ensuing from the review process, scale development and refinement, design of questionnaires, programming complex online surveys, selection of departmental statistical software, expert testimony, and adjudicating about causal inferences.
My areas of interest in statistics include multilevel modeling, latent variables, scale development and refinement, causality, scienfic transparency, replicability and reproducible research.
Distinguishing features
Work on a variety of statistical languages and software such as R, MPlus, SAS, SPSS, Stata, GeNIe and G*Power.
Work with the state of the art of collaboration tools such as GitHub, R Markdown, Shiny, Plotly and LaTeX.
Strong background in social sciences, holding a Master of Science degree in Political Science and in Social Psychology, also from Leiden University.
Reasonable fares, especially when compared with the industry's standard.
Contact
Please leave your coordinates and a brief description about the project and I shall contact you.