My Research
I am a PhD candidate in the research project 'No Data Left Behind: New meta-analytic structural equation models for complex data structures'. This project is funded through the VIDI grant awarded to Dr. Suzanne Jak. In this project, we aim to broaden the scope of research questions that can be answered through meta-analytical structural equation modeling (MASEM). In particular, I investigate the possibilities of synthesizing raw datasets, instead of summary statistics, when conducting MASEM.
Conducting MASEM on raw data is called IPD MASEM. In my view, IPD MASEM can be seen as the final stage of the evolution of meta-analysis. In order to illustrate this, I quote Gene Glass, the spiritual founder of meta-analysis:
"Meta-analysis was created out of the need to extract useful information from the cryptic records of inferential data analyses in the abbreviated reports of research in journals and other printed sources. 'What does this t-test really say about the efficacy of ritalin in comparison to caffeine?' Meta-analysis needs to be replaced by archives of raw data that permit the construction of complex data landscapes that depict the relationships among independent, dependent and mediating variables. We wish to be able to answer the question, 'What is the response of males ages 5-8 to ritalin at these dosage levels on attention, acting out and academic achievement after one, three, six and twelve months of treatment?' We can move toward this vision of useful synthesized archives of research now if we simply re-orient our ideas about what we are doing when we do research. We are not testing grand theories, rather we are charting dosage-response curves for technological interventions under a variety of circumstances. We are not informing colleagues that our straw-person null hypothesis has been rejected at the .01 level, rather we are sharing data collected and reported according to some commonly accepted protocols. We aren't publishing "studies," rather we are contributing to data archives."
Working on techniques for IPD MASEM, is an effort to allow researchers to synthesize these growing data archives to answer the most complex research questions.
