Statistical procedures and the justification of knowledge in psychological science.

1992 ◽  
pp. 295-314 ◽  
Author(s):  
Ralph L. Rosnow ◽  
Robert Rosenthal
Keyword(s):  
Statistical Procedures ◽  
Psychological Science

Embracing variability and complexity and the explanatory reductionism of scientific realism

2021 ◽  
Vol 31 (3) ◽  
pp. 417-422
Author(s):  
David C. Witherington ◽  
Timothy I. Vandiver ◽  
Jacob A. Spinks
Keyword(s):  
Human Behavior ◽  
Scientific Realism ◽  
Complex Dynamics ◽  
Intraindividual Variability ◽  
Explanatory Pluralism ◽  
Statistical Procedures ◽  
Psychological Science ◽  
Individual Human ◽  
Relational Paradigm

We agree with Arocha’s criticism of psychological science’s reliance on statistical procedures that factor out intraindividual variability and the complex dynamics inherent to behavior, as well as with his call for the adoption of a metatheoretical framework that embraces such variability. However, we disagree that scientific realism provides such a framework, given its reductive privileging of certain forms of explanation over others. We advocate, instead, a process-relational paradigm and the explanatory pluralism that it supports, allowing psychological science to more dynamically, and realistically, model individual human behavior.

A pragmatist philosophy of psychological science and its implications for replication

2018 ◽  
Vol 41 ◽  
Author(s):  
Ana Gantman ◽  
Robin Gomila ◽  
Joel E. Martinez ◽  
J. Nathan Matias ◽  
Elizabeth Levy Paluck ◽  
...  
Keyword(s):  
William James ◽  
Mental Processes ◽  
Psychological Science ◽  
Behavioral Measurement ◽  
The World ◽  
Pragmatist Philosophy

AbstractA pragmatist philosophy of psychological science offers to the direct replication debate concrete recommendations and novel benefits that are not discussed in Zwaan et al. This philosophy guides our work as field experimentalists interested in behavioral measurement. Furthermore, all psychologists can relate to its ultimate aim set out by William James: to study mental processes that provide explanations for why people behave as they do in the world.

Replications can cause distorted belief in scientific progress

2018 ◽  
Vol 41 ◽  
Author(s):  
Michał Białek
Keyword(s):  
Real World ◽  
Scientific Progress ◽  
The Public ◽  
Psychological Science

AbstractIf we want psychological science to have a meaningful real-world impact, it has to be trusted by the public. Scientific progress is noisy; accordingly, replications sometimes fail even for true findings. We need to communicate the acceptability of uncertainty to the public and our peers, to prevent psychology from being perceived as having nothing to say about reality.

Which Data to Meta-Analyze, and How?

2019 ◽  
Vol 227 (1) ◽  
pp. 64-82 ◽  
Author(s):  
Martin Voracek ◽  
Michael Kossmeier ◽  
Ulrich S. Tran
Keyword(s):  
Empirical Research ◽  
Meta Analysis ◽  
Curve Analysis ◽  
Research Progress ◽  
Primary Data ◽  
Statistical Procedures ◽  
Graphical Displays ◽  
Primary Data Analysis ◽  
Meta Analyses ◽  
Data Analytic

Abstract. Which data to analyze, and how, are fundamental questions of all empirical research. As there are always numerous flexibilities in data-analytic decisions (a “garden of forking paths”), this poses perennial problems to all empirical research. Specification-curve analysis and multiverse analysis have recently been proposed as solutions to these issues. Building on the structural analogies between primary data analysis and meta-analysis, we transform and adapt these approaches to the meta-analytic level, in tandem with combinatorial meta-analysis. We explain the rationale of this idea, suggest descriptive and inferential statistical procedures, as well as graphical displays, provide code for meta-analytic practitioners to generate and use these, and present a fully worked real example from digit ratio (2D:4D) research, totaling 1,592 meta-analytic specifications. Specification-curve and multiverse meta-analysis holds promise to resolve conflicting meta-analyses, contested evidence, controversial empirical literatures, and polarized research, and to mitigate the associated detrimental effects of these phenomena on research progress.

Translocation Relative to Range

Methodology ◽  
2008 ◽  
Vol 4 (3) ◽  
pp. 132-138 ◽  
Author(s):  
Michael Höfler
Keyword(s):  
Risk Difference ◽  
Binary Outcomes ◽  
Number Needed To Treat ◽  
Likert Scales ◽  
Psychological Science ◽  
The Absolute ◽  
The Difference ◽  
Variance Parameters ◽  
Standardized Index ◽  
Maximum Possible Magnitude

A standardized index for effect intensity, the translocation relative to range (TRR), is discussed. TRR is defined as the difference between the expectations of an outcome under two conditions (the absolute increment) divided by the maximum possible amount for that difference. TRR measures the shift caused by a factor relative to the maximum possible magnitude of that shift. For binary outcomes, TRR simply equals the risk difference, also known as the inverse number needed to treat. TRR ranges from –1 to 1 but is – unlike a correlation coefficient – a measure for effect intensity, because it does not rely on variance parameters in a certain population as do effect size measures (e.g., correlations, Cohen’s d). However, the use of TRR is restricted on outcomes with fixed and meaningful endpoints given, for instance, for meaningful psychological questionnaires or Likert scales. The use of TRR vs. Cohen’s d is illustrated with three examples from Psychological Science 2006 (issues 5 through 8). It is argued that, whenever TRR applies, it should complement Cohen’s d to avoid the problems related to the latter. In any case, the absolute increment should complement d.

Lessons learned from a life in psychological science: Implications for young scientists.

1999 ◽  
Vol 54 (2) ◽  
pp. 106-116 ◽  
Author(s):  
Frederick P. Morgeson ◽  
Martin E. P. Seligman ◽  
Robert J. Sternberg ◽  
Shelley E. Taylor ◽  
Christina M. Manning
Keyword(s):  
Lessons Learned ◽  
Psychological Science

Approaching psychological science with Kuhn's eyes.

2004 ◽  
Vol 59 (4) ◽  
pp. 272-273 ◽  
Author(s):  
Todd B. Kashdan ◽  
Michael F. Steger
Keyword(s):  
Psychological Science
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