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How I Learned to Stop Worrying and Love Replication Failures
1Department of Psychology, West Virginia University, Morgantown, WV 26506-6040 USA.
Abstract:
Worries about the reproducibility of experiments in the behavioral and social sciences arise from evidence that many published reports contain false positive results. Misunderstanding and misuse of statistical procedures are key sources of false positives. In behavior analysis, however, statistical procedures have not been used much. Instead, the investigator must show that the behavior of an individual is consistent over time within an experimental condition, that the behavior changes systematically across conditions, and that these changes can be reproduced - and then the whole pattern must be shown in additional individuals. These high standards of within- and between-subject replication protect behavior analysis from the publication of false positive findings. When a properly designed and executed experiment fails to replicate a previously published finding, the failure exposes flaws in our understanding of the phenomenon under study - perhaps in recognizing the boundary conditions of the phenomenon, identifying the relevant variables, or bringing the variables under sufficient control. We must accept the contradictory findings as valid and pursue an experimental analysis of the possible reasons. In this way, we resolve the contradiction and advance our science. To illustrate, two research programs are described, each initiated because of a replication failure.
Insights
Behavior analysis avoids false positives through rigorous within- and between-subject replication, unlike other social sciences. Replication failures drive scientific advancement by revealing flaws in understanding and control.
Area of Science:
- Behavioral and social sciences
- Behavior analysis
Background:
- Concerns regarding reproducibility in social sciences stem from frequent false positive results.
- Misuse of statistical procedures is a primary cause of false positives in research.
Purpose of the Study:
- To highlight the robust replication standards in behavior analysis.
- To explain how behavior analysis prevents false positive findings.
- To demonstrate how replication failures advance scientific understanding.
Main Methods:
- Behavior analysis relies on demonstrating behavioral consistency within conditions.
- Systematic behavioral changes across conditions are analyzed.
- Within- and between-subject replications are crucial for validating findings.
Main Results:
- High replication standards in behavior analysis minimize false positive publications.
- Replication failures expose limitations in understanding phenomena or controlling variables.
- Contradictory findings are treated as valid starting points for further experimental analysis.
Conclusions:
- Behavior analysis's stringent replication protocols safeguard against false positives.
- Replication failures are essential for scientific progress, prompting deeper investigation.
- Investigating replication failures leads to refined theories and improved experimental control.
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