An M – Stage Hierachical Group Testing Model for Estimating Multiple Traits in a Population

Monitoring the presence or absence of a trait in a large population one – at – a – time is tedious, uneconomical and bound to errors. The remedy is to group the population into homogeneous groups and test each group for the presence of a trait. Multi – stage group testing procedure involves testing groups for the presence or absence of trait in a population and sequentially subdividing the positive groups into sub – groups. The sub – groups to be tested at a particular stage are based on the information obtained from the previous stage. This paper proposed an M – stage hierarchical design for testing the presence of multiple traits in a finite population. The design improves the efficiency of the estimators as evident via the computation of asymptotic variance.