Colloquium

Colloquium


Dissertation Proposal
February 14 (Fri) 11 a.m.
Alavi Commons Room, 6625 Everett Tower

Inference on differences between k means for data with excess zeros and detection limits

Haolai Jiang
Department of Statistics
Western Michigan University

Many data have excess zeros or unobservable values falling below detection limit. For example, data on hospitalization costs incurred by members of a health insurance plan will have zeros for the percentage who did not get sick. Benzene exposure measurements on petroleum refinery workers have some exposures fall below the limit of detection. Traditional methods of inference like one-way ANOVA are not appropriate to analyze such data since the point mass at zero violates typical distribution assumptions.

For testing for equality of means of k distributions, we will propose a likelihood ratio test that accounts for excess zeros or detection limits. We will conduct simulations to study finite sample properties of the proposed procedure.

All statistics students are expected to attend.

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