Abstract
Statistical training helps individuals analyze and interpret data. However, the emphasis placed on null hypothesis significance testing in academic training and reporting may lead researchers to interpret evidence dichotomously rather than continuously. Consequently, researchers may either disregard evidence that fails to attain statistical significance or undervalue it relative to evidence that attains statistical significance. Surveys of researchers across a wide variety of fields (including medicine, epidemiology, cognitive science, psychology, business, and economics) show that a substantial majority does indeed do so. This phenomenon is manifest both in researchers' interpretations of descriptions of evidence and in their likelihood judgments. Dichotomization of evidence is reduced though still present when researchers are asked to make decisions based on the evidence, particularly when the decision outcome is personally consequential. Recommendations are offered.
Original language | English (US) |
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Pages (from-to) | 1707-1718 |
Number of pages | 12 |
Journal | Management Science |
Volume | 62 |
Issue number | 6 |
DOIs | |
State | Published - Jun 2016 |
Keywords
- Choice
- Description
- Evaluation of evidence
- Inference
- Judgment
- Null hypothesis
- Significance testing
- Sociology of science
- Strength of evidence
- p-values
ASJC Scopus subject areas
- Strategy and Management
- Management Science and Operations Research