Indiana University-Purdue University Indianapolis (IUPUI) / Randomized studies are designed to estimate the average treatment effect (ATE)
of an intervention. Individuals may derive quantitatively, or even qualitatively, different
effects from the ATE, which is called the heterogeneity of treatment effect. It is important
to detect the existence of heterogeneity in the treatment responses, and identify the
different sub-populations. Two corresponding statistical methods will be discussed in this
talk: a hypothesis testing procedure and a mixture-model based approach. The
hypothesis testing procedure was constructed to test for the existence of a treatment effect
in sub-populations. The test is nonparametric, and can be applied to all types of outcome
measures. A key innovation of this test is to build stochastic search into the test statistic
to detect signals that may not be linearly related to the multiple covariates. Simulations
were performed to compare the proposed test with existing methods. Power calculation
strategy was also developed for the proposed test at the design stage. The mixture-model
based approach was developed to identify and study the sub-populations with different
treatment effects from an intervention. A latent binary variable was used to indicate
whether or not a subject was in a sub-population with average treatment benefit. The
mixture-model combines a logistic formulation of the latent variable with proportional
hazards models. The parameters in the mixture-model were estimated by the EM
algorithm. The properties of the estimators were then studied by the simulations. Finally,
all above methods were applied to a real randomized study in a low ejection fraction population that compared the Implantable Cardioverter Defibrillator (ICD) with
conventional medical therapy in reducing total mortality.
| Identifer | oai:union.ndltd.org:IUPUI/oai:scholarworks.iupui.edu:1805/10995 |
| Date | 25 September 2015 |
| Creators | Taft, Lin H. |
| Contributors | Shen, Changyu, Li, Xiaochun, Chen, Peng-Sheng, Wessel, Jennifer |
| Source Sets | Indiana University-Purdue University Indianapolis |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
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