Questionable Research Practices (QRPs) and Their Devastating Scientific Effects

2021 ◽  
pp. 56-90
Author(s):  
R. Barker Bausell
Keyword(s):  
Publication Bias ◽  
False Positive ◽  
Institutional Research ◽  
Research Practices ◽  
Questionable Research Practices ◽  
Research Participants ◽  
Positive Results ◽  
Exhaustive List

The linchpin of both publication bias and irreproducibility involves an exhaustive list of more than a score of individually avoidable questionable research practices (QRPs) supplemented by 10 inane institutional research practices. While these untoward effects on the production of false-positive results are unsettling, a far more entertaining (in a masochistic sort of way) pair of now famous iconoclastic experiments conducted by Simmons, Nelson, and Simonsohn are presented in which, with the help of only a few well-chosen QRPs, research participants can actually become older after simply listening to a Beatle’s song. In addition, surveys designed to estimate the prevalence of these and other QRPs in the published literatures are also described.

False-Positive Results and a Nontechnical Overview of Their Modeling

2021 ◽  
pp. 39-55
Author(s):  
R. Barker Bausell
Keyword(s):  
False Positive ◽  
Statistical Power ◽  
Research Literature ◽  
Effect Sizes ◽  
P Value ◽  
Research Practices ◽  
P Values ◽  
Questionable Research Practices ◽  
Larger Sample ◽  
Positive Results

This chapter explores three empirical concepts (the p-value, the effect size, and statistical power) integral to the avoidance of false positive scientific. Their relationship to reproducibility is explained in a nontechnical manner without formulas or statistical jargon, with p-values and statistical power presented in terms of probabilities from zero to 1.0 with the values of most interest to scientists being 0.05 (synonymous with a positive, hence, publishable result) and 0.80 (the most commonly recommended probability that a positive result will be obtained if the hypothesis that generated it was correct and the study will be properly designed and conducted). Unfortunately many scientists circumvent both by artifactually inflating the 0.05 criterion, overstating the available statistical power, and engaging in a number of other questionable research practices. These issues are discussed via statistical models from the genetic and psychological fields and then extended to a number of different p-values, statistical power levels, effect sizes, and the prevalence of “true,” effects expected to exist in the research literature. Among the basic conclusions of these modeling efforts are that employing more stringent p-values and larger sample sizes constitute the most effective statistical approaches for increasing the reproducibility of published results in all empirically based scientific literatures. This chapter thus lays the necessary foundation for understanding and appreciating the effects of appropriate p-values, sufficient statistical power, reaslistic effect sizes, and the avoidance of questionable research practices upon the production of reproducible results.

scholarly journals Excess success in “Don’t count calorie labeling out: Calorie counts on the left side of menu items lead to lower calorie food choices”

2019 ◽  
Author(s):  
Gregory Francis ◽  
Evelina Thunell
Keyword(s):  
Success Rate ◽  
Publication Bias ◽  
Food Choices ◽  
Effect Sizes ◽  
Sample Sizes ◽  
Research Practices ◽  
Policy Makers ◽  
Questionable Research Practices ◽  
Calorie Labeling

Based on findings from six experiments, Dallas, Liu & Ubel (2019) concluded that placing calorie labels to the left of menu items influences consumers to choose lower calorie food options. Contrary to previously reported findings, they suggested that calorie labels do influence food choices, but only when placed to the left because they are in this case read first. If true, these findings have important implications for the design of menus and may help address the obesity pandemic. However, an analysis of the reported results indicates that they seem too good to be true. We show that if the effect sizes in Dallas et al. (2019) are representative of the populations, a replication of the six studies (with the same sample sizes) has a probability of only 0.014 of producing uniformly significant outcomes. Such a low success rate suggests that the original findings might be the result of questionable research practices or publication bias. We therefore caution readers and policy makers to be skeptical about the results and conclusions reported by Dallas et al. (2019).

scholarly journals How reliable are scientific studies?

2010 ◽  
Vol 197 (4) ◽  
pp. 257-258 ◽  
Author(s):  
Marcus R. Munafò ◽  
Jonathan Flint
Keyword(s):  
Empirical Evidence ◽  
Publication Bias ◽  
False Positive ◽  
Scientific Research ◽  
Substantial Proportion ◽  
Number Of Factors ◽  
Positive Results

SummaryThere is growing concern that a substantial proportion of scientific research may in fact be false. A number of factors have been proposed as contributing to the presence of a large number of false-positive results in the literature, one of which is publication bias. We discuss empirical evidence for these factors.

scholarly journals Correcting for Bias in Psychology: A Comparison of Meta-Analytic Methods

2019 ◽  
Vol 2 (2) ◽  
pp. 115-144 ◽  
Author(s):  
Evan C. Carter ◽  
Felix D. Schönbrodt ◽  
Will M. Gervais ◽  
Joseph Hilgard
Keyword(s):  
Publication Bias ◽  
Large Scale ◽  
Meta Analysis ◽  
Sensitivity Analyses ◽  
Simulation Studies ◽  
Research Practices ◽  
Simulation Code ◽  
Questionable Research Practices ◽  
Analytic Methods ◽  
Primary Literature

Publication bias and questionable research practices in primary research can lead to badly overestimated effects in meta-analysis. Methodologists have proposed a variety of statistical approaches to correct for such overestimation. However, it is not clear which methods work best for data typically seen in psychology. Here, we present a comprehensive simulation study in which we examined how some of the most promising meta-analytic methods perform on data that might realistically be produced by research in psychology. We simulated several levels of questionable research practices, publication bias, and heterogeneity, and used study sample sizes empirically derived from the literature. Our results clearly indicated that no single meta-analytic method consistently outperformed all the others. Therefore, we recommend that meta-analysts in psychology focus on sensitivity analyses—that is, report on a variety of methods, consider the conditions under which these methods fail (as indicated by simulation studies such as ours), and then report how conclusions might change depending on which conditions are most plausible. Moreover, given the dependence of meta-analytic methods on untestable assumptions, we strongly recommend that researchers in psychology continue their efforts to improve the primary literature and conduct large-scale, preregistered replications. We provide detailed results and simulation code at https://osf.io/rf3ys and interactive figures at http://www.shinyapps.org/apps/metaExplorer/ .

scholarly journals Registered Reports in Special Education: Introduction to the Special Series

2021 ◽  
pp. 074193252199645
Author(s):  
Bryan G. Cook ◽  
Daniel M. Maggin ◽  
Rachel E. Robertson
Keyword(s):  
Special Education ◽  
Publication Bias ◽  
Innovative Approach ◽  
Additional Time ◽  
Research Practices ◽  
Questionable Research Practices ◽  
Constructive Feedback ◽  
Special Series ◽  
Research Questions

This article introduces a special series of registered reports in Remedial and Special Education. Registered reports are an innovative approach to publishing that aim to increase the credibility of research. Registered reports are provisionally accepted for publication before a study is conducted, based on the importance of the research questions and the rigor of the proposed methods. If provisionally accepted, the journal agrees to publish the study if researchers adhere to accepted plans and report the study appropriately, regardless of study findings. In this article, we describe how registered reports work, review their benefits (e.g., combatting questionable research practices and publication bias, allowing expert reviewers to provide constructive feedback before a study is conducted) and limitations (e.g., requires additional time and effort, cannot be applied to all studies), review the application of registered reports in education and special education, and make recommendations for implementing registered reports in special education.

scholarly journals Registered Reports in Special Education: Introduction to the Special Series

2021 ◽  
Author(s):  
Bryan G. Cook ◽  
Daniel Maggin ◽  
Rachel Robertson
Keyword(s):  
Special Education ◽  
Publication Bias ◽  
Innovative Approach ◽  
Additional Time ◽  
Research Practices ◽  
Questionable Research Practices ◽  
Constructive Feedback ◽  
Special Series ◽  
Research Questions

This paper introduces a special series of registered reports in Remedial and Special Education. Registered reports are an innovative approach to publishing that aim to increase the credibility of research. Registered reports are provisionally accepted for publication before a study is conducted, based on the importance of the research questions and the rigor of the proposed methods. If provisionally accepted, the journal agrees to publish the study if researchers adhere to accepted plans and report the study appropriately, regardless of study findings. In this article, we describe how registered reports work, review their benefits (e.g., combatting questionable research practices and publication bias, allowing expert reviewers to provide constructive feedback before a study is conducted) and limitations (e.g., requires additional time and effort, cannot be applied to all studies), review the application of registered reports in education and special education, and make recommendations for implementing registered reports in special education.

scholarly journals Announcing a New Registered Report Article Type at the Journal of Speech, Language, and Hearing Research

2022 ◽  
pp. 1-4
Author(s):  
Holly L. Storkel ◽  
Frederick J. Gallun
Keyword(s):  
Peer Review ◽  
Publication Bias ◽  
Peer Review Process ◽  
Research Integrity ◽  
Research Practices ◽  
Scientific Publications ◽  
Hearing Research ◽  
Questionable Research Practices ◽  
Structural Problems ◽  
Article Type

Purpose: This editorial introduces the new registered reports article type for the Journal of Speech, Language, and Hearing Research . The goal of registered reports is to create a structural solution to address issues of publication bias toward results that are unexpected and sensational, questionable research practices that are used to produce novel results, and a peer-review process that occurs at the end of the research process when changes in fundamental design are difficult or impossible to implement. Conclusion: Registered reports can be a positive addition to scientific publications by addressing issues of publication bias, questionable research practices, and the late influence of peer review. This article type does so by requiring reviewers and authors to agree in advance that the experimental design is solid, the questions are interesting, and the results will be publishable regardless of the outcome. This procedure ensures that replication studies and null results make it into the published literature and that authors are not incentivized to alter their analyses based on the results that they obtain. Registered reports represent an ongoing commitment to research integrity and finding structural solutions to structural problems inherent in a research and publishing landscape in which publications are such a high-stakes aspect of individual and institutional success.

Publication bias and statistical power in gerontological psychology

2018 ◽  
Author(s):  
Christopher Brydges
Keyword(s):  
Publication Bias ◽  
Statistical Power ◽  
Research Practices ◽  
P Values ◽  
Questionable Research Practices ◽  
Gerontological Research ◽  
Article Type ◽  
Research Findings ◽  
Psychological Journal ◽  
Published Research

Objectives: Research has found evidence of publication bias, questionable research practices (QRPs), and low statistical power in published psychological journal articles. Isaacowitz’s (2018) editorial in the Journals of Gerontology Series B, Psychological Sciences called for investigation of these issues in gerontological research. The current study presents meta-research findings based on published research to explore if there is evidence of these practices in gerontological research. Method: 14,481 test statistics and p values were extracted from articles published in eight top gerontological psychology journals since 2000. Frequentist and Bayesian caliper tests were used to test for publication bias and QRPs (specifically, p-hacking and incorrect rounding of p values). A z-curve analysis was used to estimate average statistical power across studies.Results: Strong evidence of publication bias was observed, and average statistical power was approximately .70 – below the recommended .80 level. Evidence of p-hacking was mixed. Evidence of incorrect rounding of p values was inconclusive.Discussion: Gerontological research is not immune to publication bias, QRPs, and low statistical power. Researchers, journals, institutions, and funding bodies are encouraged to adopt open and transparent research practices, and using Registered Reports as an alternative article type to minimize publication bias and QRPs, and increase statistical power.

scholarly journals Correcting for bias in psychology: A comparison of meta-analytic methods

2017 ◽  
Author(s):  
Evan C Carter ◽  
Felix D. Schönbrodt ◽  
Will M Gervais ◽  
Joseph Hilgard
Keyword(s):  
Publication Bias ◽  
Large Scale ◽  
Meta Analysis ◽  
Sensitivity Analyses ◽  
Simulation Studies ◽  
Research Practices ◽  
Simulation Code ◽  
Questionable Research Practices ◽  
Analytic Methods ◽  
Primary Literature

Publication bias and questionable research practices in primary research can lead to badly overestimated effects in meta-analysis. Methodologists have proposed a variety of statistical approaches to correct for such overestimation. However, much of this work has not been tailored specifically to psychology, so it is not clear which methods work best for data typically seen in our field. Here, we present a comprehensive simulation study to examine how some of the most promising meta-analytic methods perform on data that might realistically be produced by research in psychology. We created such scenarios by simulating several levels of questionable research practices, publication bias, heterogeneity, and using study sample sizes empirically derived from the literature. Our results clearly indicated that no single meta-analytic method consistently outperformed all others. Therefore, we recommend that meta-analysts in psychology focus on sensitivity analyses—that is, report on a variety of methods, consider the conditions under which these methods fail (as indicated by simulation studies such as ours), and then report how conclusions might change based on which conditions are most plausible. Moreover, given the dependence of meta-analytic methods on untestable assumptions, we strongly recommend that researchers in psychology continue their efforts on improving the primary literature and conducting large-scale, pre-registered replications. We provide detailed results and simulation code at https://osf.io/rf3ys and interactive figures at http://www.shinyapps.org/apps/metaExplorer/.

scholarly journals Psychology and Law, Meet Open Science

2021 ◽  
Author(s):  
Bradley David McAuliff ◽  
Melanie B. Fessinger ◽  
Anthony Perillo ◽  
Jennifer Torkildson Perillo
Keyword(s):  
Open Access ◽  
False Positive ◽  
Psychological Research ◽  
Open Science ◽  
Open Access Publishing ◽  
Next Generation ◽  
Research Practices ◽  
Questionable Research Practices ◽  
Psychology And Law ◽  
Open Materials

As the field of psychology and law begins to embrace more transparent and accessible science, many questions arise about what open science actually is and how to do it. In this chapter, we contextualize this reform by examining fundamental concerns about psychological research—irreproducibility and replication failures, false-positive errors, and questionable research practices—that threaten its validity and credibility. Next, we turn to psychology’s response by reviewing the concept of open science and explaining how to implement specific practices—preregistration, registered reports, open materials/data/code, and open access publishing—designed to make research more transparent and accessible. We conclude by weighing the implications of open science for the field of psychology and law, specifically with respect to how we conduct and evaluate research, as well as how we train the next generation of psychological scientists and share scientific findings in applied settings.

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