Purpose: The purpose of this paper is to consider the concepts of individual and complete statistical power used for multiple testing and shows their relevance for determining the number of statistical tests to perform when assessing non-response bias.
Design/methodology/approach: A statistical power analysis of 55 survey-based research papers published in three prestigious logistics journals (International Journal of Physical Distribution and Logistics Management, Journal of Business Logistics, Transportation Journal) over the last decade was conducted.
Findings Results: show that some of the low complete power levels encountered could have been avoided if fewer tests had been used in the assessment of non-response bias.
Originality/value: The research offers important recommendations to scholars engaged in survey research as they assess the effects of non-respondents on research findings. By following the recommended strategies for testing non-response bias, researchers can improve the statistical power of their findings.
Available at: http://works.bepress.com/toyin-clottey/3/