Strong inference

2019 ◽  
pp. 1-12
Author(s):  
Nick Stergiou
Keyword(s):  
Strong Inference

What Psychology as a Science Owes Neal Miller: The Example of His Biofeedback Research

Biofeedback ◽  
2010 ◽  
Vol 38 (3) ◽  
pp. 108-117 ◽  
Author(s):  
Edward Taub
Keyword(s):  
Case History ◽  
Scientific Research ◽  
History Of ◽  
Strong Inference ◽  
Biofeedback Research

Abstract Neal Miller did more to make psychology a science than any other investigator. His importance does not lie with any specific discoveries that he made, but rather with his way of doing scientific research, which involved pursuing a line of logic systematically through sequences of experiments, and paying attention to several alternate hypotheses that could answer each of the experimental questions addressed. His approach was a model of what has been called “Strong Inference” and that is characteristically used in the hard sciences. His biofeedback research is used as a case history of his method of approach.

scholarly journals Mutual assessment during ritualized fighting in mantis shrimp (Stomatopoda)

2018 ◽  
Vol 285 (1871) ◽  
pp. 20172542 ◽  
Author(s):  
P. A. Green ◽  
S. N. Patek
Keyword(s):  
Body Size ◽  
Network Analysis ◽  
Experimental Tests ◽  
Theoretical Models ◽  
Resource Holding Potential ◽  
Self Assessment ◽  
Mantis Shrimp ◽  
Behavioural Analysis ◽  
Survival And Reproduction ◽  
Strong Inference

Safe and effective conflict resolution is critical for survival and reproduction. Theoretical models describe how animals resolve conflict by assessing their own and/or their opponent's ability (resource holding potential, RHP), yet experimental tests of these models are often inconclusive. Recent reviews have suggested this uncertainty could be alleviated by using multiple approaches to test assessment models. The mantis shrimp Neogonodactylus bredini presents visual displays and ritualistically exchanges high-force strikes during territorial contests. We tested how N. bredini contest dynamics were explained by any of three assessment models—pure self-assessment, cumulative assessment and mutual assessment—using correlations and a novel, network analysis-based sequential behavioural analysis. We staged dyadic contests over burrow access between competitors matched either randomly or based on body size. In both randomly and size-matched contests, the best metric of RHP was body mass. Burrow residency interacted with mass to predict outcome. Correlations between contest costs and RHP rejected pure self-assessment, but could not fully differentiate between cumulative and mutual assessment. The sequential behavioural analysis ruled out cumulative assessment and supported mutual assessment. Our results demonstrate how multiple analyses provide strong inference to tests of assessment models and illuminate how individual behaviours constitute an assessment strategy.

The Scientific Hypothesis Today

2019 ◽  
pp. 31-60
Author(s):  
Bradley E. Alger
Keyword(s):  
Scientific Method ◽  
Karl Popper ◽  
Major Focus ◽  
Critical Rationalism ◽  
Multiple Hypotheses ◽  
Scientific Hypothesis ◽  
Strong Inference ◽  
Key Features ◽  
Definition Of ◽  
Good Hypothesis

Chapter 2 begins by reviewing the concept of the Scientific Method, as well as many outdated definitions of “hypothesis.” The discussion leads to the modern definition of the hypothesis as a conjectural explanation for a phenomenon; it is testable and falsifiable. The hypothesis serves as a blueprint and a summary of an investigation. Certain criticisms of the hypothesis and hypothesis-driven research are based on the older definitions of the term, and the book returns to them later. This chapter identifies and defines, with simple, nontechnical examples, concepts associated with the hypothesis, such as prediction and direct and indirect measurements. The philosophical programs of Karl Popper and John Platt, Critical Rationalism and Strong Inference, respectively, form a major focus of the chapter. The chapter explores the complexities of the concepts of falsification and corroboration and the importance of having multiple hypotheses. The chapter introduces the idea of the implicit hypothesis and ends with the presentation and discussion of key features of a good hypothesis.

Strong Inference in Psychophysiological Science

2016 ◽  
pp. 3-15 ◽  
Author(s):  
John T. Cacioppo ◽  
Louis G. Tassinary ◽  
Gary G. Berntson
Keyword(s):  
Strong Inference

scholarly journals More on strong inference

2008 ◽  
Vol 5 (5) ◽  
pp. 239-239
Author(s):  
Vincent T DeVita
Keyword(s):  
Strong Inference

Whatever Happened to Theory Testing In Sport Psychology?

1983 ◽  
Vol 5 (2) ◽  
pp. 135-151 ◽  
Author(s):  
Daniel M. Landers
Keyword(s):  
Sport Psychology ◽  
Null Hypothesis ◽  
Research Method ◽  
Historical Perspective ◽  
Applied Research ◽  
Theory Testing ◽  
Laboratory Setting ◽  
Null Hypothesis Testing ◽  
Strong Inference ◽  
Meta Analyses

It is maintained that a balance among theory testing, applied research, and dissemination, though an ideal goal for sport psychology, is not being achieved because theory testing has not kept pace. To explain the rise and decline of theory testing in sport psychology a historical perspective was used. Whereas sport psychology from 1950-1965 was characterized by empiricism, from 1966-1976 it was characterized by a social analysis approach used to test single theories with novel tasks in a laboratory setting. In contrast to the earlier approaches, it is recommended that contemporary sport psychologists (a) use more meta-analyses to recheck the conclusions of past reviews, (b) become less reliant on a single research method or setting, (c) avoid premature commitments to a theory, and (d) become less enamored with statistically based null hypothesis testing. A number of suggestions are offered and examples provided to encourage, where appropriate, the use of “strong inference,” a more eclectic employment of research methods and settings as well as statistical techniques to determine the strength of observed relationships.

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