Tyler VanderWeele: The Global Flourishing Study - Seeking Analytic Input

Date: 

Wednesday, February 9, 2022, 12:10pm to 1:30pm

Location: 

CGIS Knafel Building, Room K354 and Zoom

Applied Statistics Workshop presentation by Tyler J. VanderWeele, Harvard University.

Zoom linkhttps://harvard.zoom.us/j/97004196610?pwd=eGFydkF5RDRjUlk5RVcyTjV6OStUQT09
(For the participants who cannot join the session physically.)

 

Abstract: The recently launched Global Flourishing Study is a longitudinal research study being carried out in collaboration between scholars at the Human Flourishing Program at Harvard's Institute for Quantitative Social Science, Baylor’s Institute for Studies of Religion, Gallup, and the Center for Open Science.

The study will involve data collection for approximately 240,000 participants, from 22 geographically and culturally diverse countries, with nationally representative samples within each country, and with annual data collection on the same panel of individuals for five waves of data. The survey includes a rich set of questions on well-being along with demographic, social, economic, political, religious, personality, childhood, community, health and character-based questions. The data will constitute an open-access resource available to scholars throughout the world. However, in addition to what are hoped to be diverse and wide-ranging uses of the data, the primary research team intends to carry out a series of coordinated parallel pre-registered analyses. The talk will give an overview of the Global Flourishing Study itself and the flourishing framework that motivated it, along with current analysis plans for the coordinated pre-registered studies, with the aim of receiving critique, suggestions, and feedback from the Applied Statistics Workshop participants. Open questions will be put forward concerning appropriate meta-analytic summaries, confounder control with a large number of highly correlated indicators, and challenges of missing data and attrition, all while respecting complex survey weights, the limitations of existing software, and the desire to allow the utilization of multiple software packages given the size and diversity of the primary research team.