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Even well-constructed and carefully implemented sample surveys may not be answered by every Class Member. This non-response to a survey by some Class Members can pose significant problems if not identified and addressed appropriately. In some cases, incorrectly handled non-response by Class Members can undermine the entire survey. It is therefore essential that statistics based on sample surveys identify and address issues resulting from non-response before biases damage critical information. This presentation will pay special attention to how a valid statistical sample is implemented and how valid statistical results can be extracted from imperfect survey responses. Additionally, it will focus on practical tests and methods to minimize the bias that can result from non-response. Issues to be discussed will be:
- How non-response bias impacts the fundamental assumptions of scientifically based samples
- How to assess the impact of non-response on the critical survey information
- What types of methods can correct for the potential sampling problems resulting from non-response
- How to find the additional information and data that can be used to correct for the potential non-response bias
Join Dr. Daniel S. Levy, National Managing Director at Advanced Analytical Consulting Group, Inc. (AACG), as he discusses how to navigate this important statistical issue at the core of many Wage and Hour analyses, and highlights the solutions that can help you avoid a dangerous pitfall in the analysis of Wage and Hour matters.
About the Presenter: Dr. Daniel S. Levy has studied wage and hour and statistical issues in a range of industries related to litigation matters, academic research and for the US Government. Prior to joining Advanced Analytical Consulting Group (AACG), Dr. Levy held positions at Deloitte FAS and Arthur Andersen Business Solutions as the Global Leader of Economic and Statistical Consulting, and at Charles River Associates, the Rand Corporation and The University of Chicago Computation Center. He earned a Ph.D. in Economics from The University of Chicago.