Research synthesis plays a central role in the process of scientific
discovery, providing a formal methodology for the systematic accumulation
and evaluation of scientific evidence. There are many situations in which
research synthesis is required because obtaining the necessary information
from an individual trial is not possible or practical. The study of the
relationship between suicide and antidepressant use in children and
adolescents is one such case. To shed light on this issue, the FDA
combined data from 24 randomized controlled trials using standard
frequentist fixed and random effects models. However, the diversity of
the trials suggested the presence of systematic effect variation that was
not incorporated into these models. We applied a Bayesian hierarchical
model to the data to include more appropriate variance structure and
answer scientific questions regarding subsets of the data. This type of
model is sensitive to prior specification of the variance components, and
so we conducted an extensive analysis to determine the robustness of our
results. While this technique was successful in solving the variance and
subsetting issues, the collection of clinical trials share qualities that
limit the generalizability of the meta-analysis. I am investigating
extensions of research synthesis to overcome some of these limitations.
Meet the speaker in Room 212 Cockins Hall at 4:30
p.m. Refreshments will be served.