Conceptual and Statistical Knowledge

 

Significance tests have their place

Null-hypothesis significance tests (NHST), properly used, tell us whether we have sufficient evidence to be confident of the sign of the population effect–but only if we abandon two-valued logic in favor of Kaiser's (1960) three-alternative …

Statistical Power and the Testing of Null Hypotheses: A Review of Contemporary Management Research and Recommendations for Future Studies

The purpose of this study is to determine how well contemporary management research fares on the issue of statistical power with regard to studies specifically predicting null relationships between phenomena of interest. This power assessment differs …

Statistical Power Problems with Moderated Multiple Regression in Management Research

Due to the increasing importance of moderating (i.e., interaction) effects, the use of moderated multiple regression (MMR) has become pervasive in numerous management specialties such as organizational behavior, human resources management, and …

Statistical significance testing and cumulative knowledge in psychology: implications for training researchers.

Data analysis methods in psychology still emphasize statistical significance testing, despite numerous articles demonstrating its severe deficiencies. It is now possible to use meta-analysis to show that reliance on significance testing retards the …

The N-Pact Factor: Evaluating the Quality of Empirical Journals with Respect to Sample Size and Statistical Power

The authors evaluate the quality of research reported in major journals in social-personality psychology by ranking those journals with respect to their N-pact Factors (NF)—the statistical power of the empirical studies they publish to detect typical …

One cheer for null hypothesis significance testing

Null hypothesis testing as a tool in research is defended. Six examples are offered of situations in which, if all the researcher could do was "reject H₀ at α = .05" the scientific contribution would still be substantial. The examples are drawn from …

On the challenges of drawing conclusions from p-values just below 0.05

In recent years, researchers have attempted to provide an indication of the prevalence of inflated Type 1 error rates by analyzing the distribution of p-values in the published literature. De Winter & Dodou (2015) analyzed the distribution (and its …

Performing high‐powered studies efficiently with sequential analyses

Running studies with high statistical power, while effect size estimates in psychology are often inaccurate, leads to a practical challenge when designing an experiment. This challenge can be addressed by performing sequential analyses while the data …

Small telescopes Detectability and the evaluation of replication results.

This article introduces a new approach for evaluating replication results. It combines effect-size estimation with hypothesis testing, assessing the extent to which the replication results are consistent with an effect size big enough to have been …

Bite-Size Science and Its Undesired Side Effects

Short and rapid publication of research findings has many advantages. However, there is another side of the coin that needs careful consideration. We argue that the most dangerous aspect of a shift toward “bite-size” publishing is the relationship …
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