Lori Bhaskar, Indiana University

Tamara Lambert, The University of Manchester

There is a growing concern among academics that publication bias negatively affects our understanding of the phenomena studied. In auditing research, there is also concern that scarce experimental participant resources may be consumed inefficiently by continuing to test theories or research questions that have failed to be supported by data because other researchers are unaware of the respective designs and outcomes.

The Call seeks to counteract distorted inferences that might occur as a result of publication bias. Submissions could demonstrate that a potentially important result in the experimental literature is not reliably replicated or document and explore conditions under which tests that are well-supported by theory deliver results that are unexpected or not statistically significant. Publishing these results will inform the research community about the conditions under which these theories have been tested so that future research can take these designs and findings into account.

The Call aims to help auditing researchers develop a toolbox for designing, analyzing, and reporting experiments in which unexpected or non-significant results nonetheless have inferential value. Submissions could highlight methods for ensuring that a test is adequately powered, constructs are valid, and the design has sufficient internal validity so that a failure to reject the null hypothesis provides reliable information. Submissions should also develop guidelines for inference when results are not statistically significant.

Given the Call's focus on unexpected or non-significant results, submissions must address relevant topics and demonstrate a meaningful contribution to the literature. Editors will pay particular attention to issues such as the theoretical basis for the hypotheses, power and construct validity, and internal validity of the design.

Papers will be published in a Special Section of the journal as they are accepted, coordinating the timing of acceptances and space availability in individual journal issues. Submissions will be screened and assigned to handling editors, who will then assign submissions to two reviewers, consistent with AJPT's standard review process.

Potential topics

• Publication bias and experimental design in auditing research
• Replication of experimental findings and documentation of non-significant results
• Conditions under which theoretically-supported hypotheses yield unexpected or non-statistically significant outcomes
• Methods for ensuring adequate statistical power, construct validity, and internal validity in experiments
• Guidelines for inference and interpretation when results are not statistically significant
• Efficient use of experimental participant resources and research design
• Development of best practices for designing, analyzing, and reporting experiments with non-significant results

Timeline

• August 31, 2027: Deadline for submissions