Design of Experiments

Modifying quantitative methodology to support wider inferencing

The area of inquiry I pursue in STEM is the statistical design and analysis of experiments, particularly in understanding statistical tradeoffs of smaller (in general, modified) experiments. I intend to understand how it is we could design experiments with sufficient power, among other metrics, to be logistically less demanding and support inquiry and scientific productivity in low-resource contexts such as action research or high school STEM projects. My overall goal is to develop a mastery on inference strength regardless of a reduction of design parameters.

My major interests revolve around longitudinal models, such as on how we might be able to reduce resource load for designs of such. I have explored, in a related manner, the statistical tradeoffs of incomplete block designs pursued in international large-scale assessments such as PISA. I am now currently exploring the implications of how differentiated longitudinal measures are handled.

Submitted manuscripts

• Rutkowski, L., Rutkowski, D., Dolino, L. Evaluating Conditioning Model Complexity in Large-Scale Assessments: Implications for Subpopulation Comparisons.

Manuscripts in preparation

• Dolino, L.G., Tuazon, J. & Rutkowski, L. Design and implementation of reduced longitudinal experiments.