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Spring 2007
STATISTICS
COLLOQUIUM
Wednesday, February 21, 2007
3:30-4:00—Refreshments, Yost 327
4:00-5:00—Talk,
Yost, Room 101
Rhoderick Machekano, PhD
Associate Professor, CASE
Center for Health Research and Policy and Center for AIDS Research
Efficacy Studies of Malaria Treatments in Africa: Efficient Estimation with
Missing Indicators of Failure
Efficacy studies of malaria treatments can be plagued by indeterminate outcomes
for some patients. The study motivating this work defines the outcome
of interest treatment failure) as recrudescence and for some subjects, it is
unclear whether a recurrence of malaria is due to that or new infection. This
results in a specific kind of missing data. The effect of missing data in causal
inference problems is widely recognized. Methods that adjust for possible
bias from missing data include a variety of imputation procedures (extreme
case analysis, hot-deck, single and multiple imputation), inverse weighting
methods, and likelihood based methods (data augmentation, EM procedures
and their extensions). In this talk, I focus on multiple imputation, two inverse
weighting procedures (the inverse probability weighted (IPW) and the
doubly robust (DR) estimators), and a likelihood based methodology (Gcomputation),
comparing the methods’ applicability to the efficient estimation
of malaria treatments effects. I present results from simulation studies as
well as results from an application to malaria efficacy studies from Uganda.
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