SeminarsBinary Time Series Modeling with Application to Adhesion Frequency Experiments
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Cell adhesion plays an important role in many physiological and pathological processes. The only published method for measuring the kinetic rates of cell adhesion is the repeated adhesion frequency. Traditional analysis of adhesion frequency experiments assumes that the adhesion test cycles are independent Bernoulli trials. This assumption is often violated in practice. The major part of the talk will focus on a new binary time series model motivated by the analysis of repeated adhesion frequency tests. To assess the adequacy of distribution assumptions on the dependent binary data with random effects, a goodness-of-fit statistic will be proposed. The asymptotic distribution of the goodness-of-fit statistic is derived and its finite-sample performance is examined via a simulation study. Application of the proposed methodology to real data from a T-cell experiment at Georgia Tech provides some valuable information, including quantifying the memory effects in cells and molecules. This information is crucial to the body's defense in the immune system.
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Ying Hung
2008-06-17
13:30:00 - 15:00:00
501 , Freshman Classroom Building
Cell adhesion plays an important role in many physiological and pathological processes. The only published method for measuring the kinetic rates of cell adhesion is the repeated adhesion frequency. Traditional analysis of adhesion frequency experiments assumes that the adhesion test cycles are independent Bernoulli trials. This assumption is often violated in practice. The major part of the talk will focus on a new binary time series model motivated by the analysis of repeated adhesion frequency tests. To assess the adequacy of distribution assumptions on the dependent binary data with random effects, a goodness-of-fit statistic will be proposed. The asymptotic distribution of the goodness-of-fit statistic is derived and its finite-sample performance is examined via a simulation study. Application of the proposed methodology to real data from a T-cell experiment at Georgia Tech provides some valuable information, including quantifying the memory effects in cells and molecules. This information is crucial to the body's defense in the immune system.