Continuously Cumulating Meta-Analysis and Replicability

Braver, Sanford L.; Thoemmes, Felix; Rosenthal, Robert

doi:10.1177/1745691614529796

Cited by 304 publications

(327 citation statements)

References 70 publications

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“…Following recent recommendations, we conducted an internal meta-analysis of all the data collected for this project (Braver et al, 2014;Cumming, 2014;Maner, 2014;Schimmack, 2012;Stanley & Spence, 2014). This greatly improves the power of the test of the inhibitory spillover effect and provides insights in the consistency of the results obtained across studies.…”

Section: Discussionmentioning

confidence: 99%

The propagation of self-control: Self-control in one domain simultaneously improves self-control in other domains.

Tuk¹,

Zhang²,

Sweldens³

2015

Journal of Experimental Psychology: General

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A rich tradition in self-control research has documented the negative consequences of exerting self-control in one task for self-control performance in subsequent tasks. However, there is a dearth of research examining what happens when people exert self-control in multiple domains simultaneously. The current research aims to fill this gap. We integrate predictions from the most prominent models of self-control with recent neuropsychological insights in the human inhibition system to generate the novel hypothesis that exerting effortful self-control in one task can simultaneously improve self-control in completely unrelated domains. An internal meta-analysis on all 18 studies we conducted shows that exerting self-control in one domain (i.e., controlling attention, food consumption, emotions or thoughts) simultaneously improves self-control in a range of other domains, as demonstrated by, for example, reduced unhealthy food consumption, better Stroop task performance, and less impulsive decision making. A subset of nine studies demonstrates the crucial nature of task timing -when the same tasks are executed sequentially, our results suggest the emergence of an ego depletion effect. We provide conservative estimates of the self-control facilitation (d = |0.22|) as well as the ego depletion effect size (d = |0.17|) free of data selection and publication biases. These results (i) shed new light on self-control theories, (ii) confirm recent claims that previous estimates of the ego depletion effect size were inflated due to publication bias, and (iii) provide a blueprint for how to handle the power issues and associated file drawer problems commonly encountered in multi-study research projects.

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Section: Discussionmentioning

confidence: 99%

The propagation of self-control: Self-control in one domain simultaneously improves self-control in other domains.

Tuk¹,

Zhang²,

Sweldens³

2015

Journal of Experimental Psychology: General

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“…The number of abstracts is clearly insufficient to provide statistically significant results and estimates of d have a large standard error. The correct way to incorporate the results of data collected after the analysis of an initial tranche of data is via meta-analysis (Braver et al 2014). Just adding the new data to the existing data set is wrong, since it involves deciding to collect more data after looking at the results (John et al 2012).…”

Section: Phase 2 Analysismentioning

confidence: 99%

Robust Statistical Methods for Empirical Software Engineering

et al. 2016

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There have been many changes in statistical theory in the past 30 years, including increased evidence that non-robust methods may fail to detect important results. The statistical advice available to software engineering researchers needs to be updated to address these issues. This paper aims both to explain the new results in the area of robust analysis methods and to provide a large-scale worked example of the new methods. We summarise the results of analyses of the Type 1 error efficiency and power of standard parametric and non-parametric statistical tests when applied to non-normal data sets. We identify parametric and non-parametric methods that are robust to non-normality. We present an analysis of a large-scale software engineering experiment to illustrate their use. We illustrate the use of kernel density plots, and parametric and non-parametric methods using four different software engineering data sets. We explain why the methods are necessary and the rationale for selecting a specific analysis. We suggest using kernel density plots rather than box plots to visualise data distributions. For parametric analysis, we recommend trimmed means, which can support reliable tests of the differences between the central location of two or

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“…In light of increasing calls to move from evaluating single studies in isolation to considering the information provided by a cumulative body of research evidence (e.g., Braver, Thoemmes, & Rosenthal, 2014;Ledgerwood, 2014;Maner, 2014), we conducted two meta-analyses to quantitatively synthesize our key results and get a better estimate of the size of the effects in our two-part story about the function of group symbols: namely, (1) the effect of group symbol on perceived entitativity and (2) the effect of motivation on symbol display behaviors. Across all of our studies that tested the first effect (the six reported in the text and two additional studies mentioned in Footnote 3 and further below in the section on Boundary Conditions), we meta-analyzed nine effect sizes estimating the influence of symbols on perceived entitativity across a total of 907 participants.…”

Section: Meta-analysesmentioning

confidence: 99%

On the psychological function of flags and logos: Group identity symbols increase perceived entitativity.

Callahan¹,

Ledgerwood²

2016

Journal of Personality and Social Psychology

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Group identity symbols such as flags and logos have been widely used across time and cultures, yet researchers know very little about the psychological functions that such symbols can serve. The present research tested the hypotheses that (a) simply having a symbol leads collections of individuals to seem more like real, unified groups, (b) this increased psychological realness leads groups to seem more threatening and effective to others, and (c) group members therefore strategically emphasize symbols when they want their group to appear unified and intimidating. In Studies 1a–1c, participants perceived various task groups as more entitative when they happened to have a symbol. In Study 2, symbols not only helped groups make up for lacking a physical characteristic associated with entitativity (physical similarity), but also led groups to seem more threatening. Study 3 examined the processes underlying this effect and found that group symbols increase entitativity by increasing perceived cohesiveness. Study 4 extended our results to show that symbols not only shape the impressions people form of novel groups, but also change people’s existing impressions of more familiar and real-world social groups, making them seem more entitative and competent but also less warm. Finally, Studies 5a and 5b further expand our understanding of the psychological function of symbols by showing that group members strategically display symbols when they are motivated to convey an impression of their group as unified and threatening (vs. inclusive and cooperative). We discuss implications for understanding how group members navigate their social identities.

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Continuously Cumulating Meta-Analysis and Replicability

Cited by 304 publications

References 70 publications

The propagation of self-control: Self-control in one domain simultaneously improves self-control in other domains.

The propagation of self-control: Self-control in one domain simultaneously improves self-control in other domains.

Robust Statistical Methods for Empirical Software Engineering

On the psychological function of flags and logos: Group identity symbols increase perceived entitativity.

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