Large-sample hypothesis tests for stratified group-testing data

Article

DOI: 10.1198/108571107X250977

Cite this article as:
Tebbs, J.M. & McCann, M.H. JABES (2007) 12: 534. doi:10.1198/108571107X250977
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Abstract

Insect-vectored plant diseases impact the agricultural community each year by affecting the economic value, the quantity, and the quality of crops. Controlling the spread of disease is an important area in risk assessment, and understanding the dynamics of vector populations helps researchers to develop effective treatments. In this article, we consider an experimental design commonly used by researchers who study plant disease and examine large-sample, likelihood-based hypothesis tests that can be used to characterize disease-transmission behavior in a stratified population. Small-sample size and power results along with design considerations are provided. We illustrate our testing procedures using two real data examples and provide recommendations for plant-disease researchers in the field.

Key Words

Asymptotically optimal tests EM algorithm Plant disease Pooled testing Vector-transfer design 

Copyright information

© International Biometric Society 2007

Authors and Affiliations

  1. 1.Department of StatisticsUniversity of South CarolinaColumbia
  2. 2.Department of StatisticsOklahoma State UniversityStillwater

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