False Negatives

Fiedler, Klaus; Schott, Malte

doi:10.1002/9781119095910.ch4

Cited by 3 publications

(4 citation statements)

References 62 publications

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“…However, the large gains associated with TPs in the medical context must also be considered (cf. Fiedler & Schott, in press), because the choice of an optimal strategy depends on the relative sizes of the payoffs—not the absolute sizes (e.g., Swets et al, 2000). In this example, there would obviously be a very large payoff for a TP (i.e., finding an effective treatment).…”

Section: Discussionmentioning

confidence: 99%

“…This is no easy task either, however. Finkel et al (2015) analyzed the debate over whether there are higher costs to FNs than to FPs, and they concluded that it depends very much on the details of the research area under discussion (also see Fiedler & Schott, in press). In medical research, for example, FNs are especially bad outcomes because they represent missed opportunities to identify helpful therapies, presumably due to some combination of low-ish study power and bad luck.…”

Section: Discussionmentioning

confidence: 99%

“…Naturally, then, concern over FPs has led to recommendations that researchers make these choices in such a way as to minimize FP frequency (e.g., Asendorpf et al, 2013; Button et al, 2013; Ioannidis, 2005b; Johnson, 2013; Nosek et al, 2012). Unfortunately, the same choices that minimize FPs necessarily have other consequences, some of which are undesirable (e.g., Fiedler et al, 2012; Fiedler & Schott, in press; Finkel et al, 2015; Friston, 2012; Ioannidis, 2014; Johnson, 2013; Mudge, Baker, Edge, & Houlahan, 2012; Sbarra, 2014). In particular, as will be elaborated later, minimizing FPs also tends to slow the discovery of real effects, known as true positives (TPs).…”

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confidence: 99%

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Optimizing Research Payoff

Miller

Ulrich

2016

Perspect Psychol Sci

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In this article, we present a model for determining how total research payoff depends on researchers' choices of sample sizes, α levels, and other parameters of the research process. The model can be used to quantify various trade-offs inherent in the research process and thus to balance competing goals, such as (a) maximizing both the number of studies carried out and also the statistical power of each study, (b) minimizing the rates of both false positive and false negative findings, and (c) maximizing both replicability and research efficiency. Given certain necessary information about a research area, the model can be used to determine the optimal values of sample size, statistical power, rate of false positives, rate of false negatives, and replicability, such that overall research payoff is maximized. More specifically, the model shows how the optimal values of these quantities depend upon the size and frequency of true effects within the area, as well as the individual payoffs associated with particular study outcomes. The model is particularly relevant within current discussions of how to optimize the productivity of scientific research, because it shows which aspects of a research area must be considered and how these aspects combine to determine total research payoff.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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confidence: 99%

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Optimizing Research Payoff

Miller

Ulrich

2016

Perspect Psychol Sci

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“…A considerable volume of social psychological findings can be summarized as “individuals avoid inconsistencies” or “inconsistencies are aversive.” However, as Fiedler and Schott (2017) point out a wealth of true positive results can sometimes lead to theory building that is over-specified. That is, a theory can be correct and supported by valid evidence, but only describe a specific case of a larger phenomenon.…”

Section: Social Verificationmentioning

confidence: 99%

Social Verification Theory: A New Way to Conceptualize Validation, Dissonance, and Belonging

Hillman

Fowlie

MacDonald

2022

Pers Soc Psychol Rev

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Academic Abstract In the present review, we propose a theory that seeks to recontextualize various existing theories as functions of people’s perceptions of their consistency with those around them. This theory posits that people seek social consistency for both epistemic and relational needs and that social inconsistency is both negative and aversive, similar to the experience of cognitive dissonance. We further posit that the aversive nature of perceiving social inconsistency leads people to engage in various behaviors to mitigate or avoid these inconsistencies. When these behaviors fail, however, people experience chronic social inconsistency, which, much like chronic rejection, is associated with physical and mental health and well-being outcomes. Finally, we describe how mitigation and avoidance of social inconsistency underlie many seemingly unrelated theories, and we provide directions for how future research may expand on this theory. Public Abstract In the present review, we propose that people find inconsistency with those around them to be an unpleasant experience, as it threatens people’s core need to belong. Because the threat of reduced belongingness evokes negative feelings, people are motivated to avoid inconsistency with others and to mitigate the negative feelings that are produced when it inevitably does arise. We outline several types of behaviors that can be implemented to avoid or mitigate these inconsistencies (e.g., validation, affirmation, distancing, etc.). When these behaviors cannot be implemented successfully, people experience chronic invalidation, which is associated with reduced physical and mental health and well-being outcomes. We discuss how invalidation may disproportionately affect individuals with minoritized identities. Furthermore, we discuss how belongingness could play a key role in radicalization into extremist groups.

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Optimizing Research Output: How Can Psychological Research Methods Be Improved?

Miller

Ulrich

2022

Annu. Rev. Psychol.

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Recent evidence suggests that research practices in psychology and many other disciplines are far less effective than previously assumed, which has led to what has been called a “crisis of confidence” in psychological research (e.g., Pashler & Wagenmakers 2012). In response to the perceived crisis, standard research practices have come under intense scrutiny, and various changes have been suggested to improve them. The burgeoning field of metascience seeks to use standard quantitative data-gathering and modeling techniques to understand the reasons for inefficiency, to assess the likely effects of suggested changes, and ultimately to tell psychologists how to do better science. We review the pros and cons of suggested changes, highlighting the many complex research trade-offs that must be addressed to identify better methods. Expected final online publication date for the Annual Review of Psychology, Volume 73 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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False Negatives

Cited by 3 publications

References 62 publications

Optimizing Research Payoff

Optimizing Research Payoff

Social Verification Theory: A New Way to Conceptualize Validation, Dissonance, and Belonging

Optimizing Research Output: How Can Psychological Research Methods Be Improved?

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