Symposium
Program Session: 1767 | Submission: 16282 | Sponsor(s): RM, OMT, OB
Tuesday, Aug 9 2016 9:45AM - 11:15AM at Anaheim Convention Center in 303C
How to Improve on Statistical Significance: Effect Sizes, CIs, Graphs and Baseline Models
Organizer & Presenter: William H. Starbuck, U. of Oregon
Organizer & Presenter: Andreas Schwab, Iowa State U.
Presenter: Samuel Holloway, U. of Portland
This symposium will introduce and discuss how scholars can improve upon the Null Hypothesis Significance Tests (NHSTs), which are currently constraining the production of knowledge in management science. The extensive use of NHST in quantitative research has led to the accumulation of "statistically significant" results that are both too small to be practically relevant and so small that they are unlikely to replicate. In a field that aspires to provide useful advice to managers, we need to focus on practically important effects that are robust across a wide variety of settings. The proposed symposium introduces and discusses alternative approaches to address NHST limitations -- such as, effect size measures, confidence intervals, graphs, and baseline modeling. A final "Question and Answer" session will offer additional opportunities for specific discussions, advice and recommendations.
Search Terms: Statistical Significance | Effect Size | Practical Significance
Andreas Schwab
Iowa State University
aschwab@iastate.edu