The name of this collaborative project is MIDDLE: Maintained Individual Data – Distributed Likelihood Estimation. The project aims to develop a new research platform for behavioral and social science research, based on the idea that data can and should be maintained and controlled by experiment participants.
An initial focus of the project is developing an "app store" for such research. The researchers will develop software through which subjects can sign up for paid experiments using their smartphones. Using this software, MIDDLE will provide a way for researchers to collect and analyze the data they need, while ensuring that subjects’ personal data remains on their own smartphones and is never shared with researchers. This is possible because, using the app, researchers will send candidate models to subjects’ smartphones, which will evaluate how well the model fits their own data. Only the model fit metric will be communicated back to researchers. In this way, statistical analysis can be conducted without revealing any personal data. MIDDLE will provide automatic management of opt-in and opt-out consent; lower research costs; and deliver faster results. Robust privacy protection will reassure participants and permit research on topics that are sensitive or involve data that must legally be kept private.
Joshua Pritikin Research Bio
Joshua is a Ph.D. student in Psychology at UVA. He has several years of experience working on the project OpenMx, which has required him to develop diverse skills as a researcher and which provides much of the programming functionality that will support the MIDDLE project. Both statistics and software engineering are challenging fields that are difficult to surmount separately, much less together, and he is confident that collaborating on this project will both improve the creativity and success of the research and allow for much faster completion of the project than one researcher could manage alone.
Advisor: Steven Boker
Yang Wang Research Bio
Yang is a first year Ph.D. student in Systems Engineering at UVA. His interests lie in the area of statistical analysis and software development, particularly in how to use and analyze big data. From the engineering perspective, this project provides a remarkable opportunity to apply knowledge and implement widely-adopted tools used in engineering research for the social science community. He expects to draw on his collaborator’s expertise in these areas while contributing his own knowledge of and facility with the research tools used, and he intends to build upon his work on this project as he crafts his own doctoral thesis.
Advisor: Donald Brown