A BINOMIAL MODEL APPROXIMATION FOR MULTIPLE TESTING

Authors

  • I. A. ADELEKE Department of Actuarial Science and Insurance, University of Lagos, Nigeria
  • A. O. ADEYEMI Department of Mathematics, University of Lagos, Nigeria
  • E. E.E. AKARAWAK Department of Mathematics, University of Lagos, Nigeria

DOI:

https://doi.org/10.51406/jnset.v16i2.1850

Keywords:

Bonferroni Procedure, False Discovery Rate, Binomial Model Approximation, False Positives, False Negatives, Multiple Testing

Abstract

Multiple testing is associated with simultaneous testing of many hypotheses, and frequently calls for adjusting level of significance in some way that the probability of observing at least one significant result due to chance remains below the desired significance levels. This study developed a Binomial Model Approximations (BMA) method as an alternative to addressing the multiplicity problem associated with testing more than one hypothesis at a time. The proposed method has demonstrated capacity for controlling Type I Error Rate as sample size increases when compared with the existing Bonferroni and False Discovery Rate (FDR).

 

 

 

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Published

2019-05-17

Issue

Vol. 16 No. 2 (2017)

Section

Articles