Blakeley B. McShane

Bio: Blakeley B. McShane is an academic researcher from Northwestern University. The author has contributed to research in topics: Replication (statistics) & Sample size determination. The author has an hindex of 23, co-authored 47 publications receiving 2418 citations. Previous affiliations of Blakeley B. McShane include University of Pennsylvania.

Abandon Statistical Significance

Abstract: We discuss problems the null hypothesis significance testing (NHST) paradigm poses for replication and more broadly in the biomedical and social sciences as well as how these problems remain unreso

Adjusting for Publication Bias in Meta-Analysis: An Evaluation of Selection Methods and Some Cautionary Notes

Abstract: We review and evaluate selection methods, a prominent class of techniques first proposed by Hedges (1984) that assess and adjust for publication bias in meta-analysis, via an extensive simulation s...

Single-paper meta-analysis: Benefits for study summary, theory testing, and replicability.

Abstract: A typical behavioral research paper features multiple studies of a common phenomenon that are analyzed solely in isolation. Because the studies are of a common phenomenon, this practice is inefficient and foregoes important benefits that be obtained only by analyzing them jointly in a single paper meta-analysis (SPM). To facilitate SPM, we introduce metaanalytic methodology that is user-friendly, widely applicable, and specially tailored to the SPM of the set of studies that appear in a typical behavioral research paper. Our SPM methodology provides important benefits for study summary, theory-testing, and replicability that we illustrate via three case studies that include papers recently published in the Journal of Consumer Research and the Journal of Marketing Research. We advocate that authors of typical behavioral research papers use it to supplement the single-study analyses that independently discuss the multiple studies in the body of their papers as well as the "qualitative meta-analysis" that verbally synthesizes the studies in the general discussion of their papers. When used as such, this requires only a minor modification of current practice. We provide an easy-to-use website that implements our SPM methodology.

Abandon Statistical Significance.

Abstract: We discuss problems the null hypothesis significance testing (NHST) paradigm poses for replication and more broadly in the biomedical and social sciences as well as how these problems remain unresolved by proposals involving modified p-value thresholds, confidence intervals, and Bayes factors. We then discuss our own proposal, which is to abandon statistical significance. We recommend dropping the NHST paradigm--and the p-value thresholds intrinsic to it--as the default statistical paradigm for research, publication, and discovery in the biomedical and social sciences. Specifically, we propose that the p-value be demoted from its threshold screening role and instead, treated continuously, be considered along with currently subordinate factors (e.g., related prior evidence, plausibility of mechanism, study design and data quality, real world costs and benefits, novelty of finding, and other factors that vary by research domain) as just one among many pieces of evidence. We have no desire to "ban" p-values or other purely statistical measures. Rather, we believe that such measures should not be thresholded and that, thresholded or not, they should not take priority over the currently subordinate factors. We also argue that it seldom makes sense to calibrate evidence as a function of p-values or other purely statistical measures. We offer recommendations for how our proposal can be implemented in the scientific publication process as well as in statistical decision making more broadly.

Single Paper Meta-Analysis: Benefits For Study Summary, Theory-Testing, and Replicability

Abstract: A typical behavioral research paper features multiple studies of a common phenomenon that are analyzed solely in isolation. Because the studies are of a common phenomenon, this practice is inefficient and foregoes important benefits that be obtained only by analyzing them jointly in a single paper meta-analysis (SPM). To facilitate SPM, we introduce metaanalytic methodology that is user-friendly, widely applicable, and specially tailored to the SPM of the set of studies that appear in a typical behavioral research paper. Our SPM methodology provides important benefits for study summary, theory-testing, and replicability that we illustrate via three case studies that include papers recently published in the Journal of Consumer Research and the Journal of Marketing Research. We advocate that authors of typical behavioral research papers use it to supplement the single-study analyses that independently discuss the multiple studies in the body of their papers as well as the "qualitative meta-analysis" that verbally synthesizes the studies in the general discussion of their papers. When used as such, this requires only a minor modification of current practice. We provide an easy-to-use website that implements our SPM methodology.

Climate Change 2007: The Physical Science Basis.

Abstract: Cause, conseguenze e strategie di mitigazione Proponiamo il primo di una serie di articoli in cui affronteremo l’attuale problema dei mutamenti climatici. Presentiamo il documento redatto, votato e pubblicato dall’Ipcc - Comitato intergovernativo sui cambiamenti climatici - che illustra la sintesi delle ricerche svolte su questo tema rilevante.

The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields (Chinese Translation)

Abstract: What makes organizations so similar? We contend that the engine of rationalization and bureaucratization has moved from the competitive marketplace to the state and the professions. Once a set of organizations emerges as a field, a paradox arises: rational actors make their organizations increasingly similar as they try to change them. We describe three isomorphic processes-coercive, mimetic, and normative—leading to this outcome. We then specify hypotheses about the impact of resource centralization and dependency, goal ambiguity and technical uncertainty, and professionalization and structuration on isomorphic change. Finally, we suggest implications for theories of organizations and social change.

Scientists rise up against statistical significance

Abstract: Valentin Amrhein, Sander Greenland, Blake McShane and more than 800 signatories call for an end to hyped claims and the dismissal of possibly crucial effects. Valentin Amrhein, Sander Greenland, Blake McShane and more than 800 signatories call for an end to hyped claims and the dismissal of possibly crucial effects.

Moving to a World Beyond “p < 0.05”

Abstract: Some of you exploring this special issue of The American Statistician might be wondering if it’s a scolding from pedantic statisticians lecturing you about what not to do with p-values, without offering any real ideas of what to do about the very hard problem of separating signal from noise in data and making decisions under uncertainty. Fear not. In this issue, thanks to 43 innovative and thought-provoking papers from forward-looking statisticians, help is on the way.