Theory Construction and Data Analysis in the Behavioral Sciences (A Volume in Honor of Louis Guttman).

1981 ◽  
Vol 76 (374) ◽  
pp. 500
Author(s):  
Thomas S. Wallsten ◽  
Samuel Shye
Keyword(s):  
Data Analysis ◽  
Theory Construction ◽  
Behavioral Sciences

Elementary Statistics: Data Analysis for the Behavioral Sciences.

1968 ◽  
Vol 33 (1) ◽  
pp. 166
Author(s):  
Donal E. Muir ◽  
Paul A. Games ◽  
George R. Klare
Keyword(s):  
Data Analysis ◽  
Behavioral Sciences ◽  
Elementary Statistics

Theory construction and data analysis

2017 ◽  
Vol 27 (1) ◽  
pp. 126-134 ◽  
Author(s):  
Warren W. Tryon ◽  
Thanos Patelis ◽  
Michael Chajewski ◽  
Charles Lewis
Keyword(s):  
Data Analysis ◽  
Empirical Evidence ◽  
Theory Construction ◽  
Mathematical Arguments ◽  
Analytic Methods ◽  
Traditional Approaches ◽  
Data Analytic

Data analysis should be neutral relative to theory construction in order to be unbiased. Data analysis should not strongly favor one form of theory construction over others. Traditional approaches to theory construction prioritize simplicity of explanation based on parsimony using a few prominent statistically significant variables. Alternative web of causation explanations prioritize comprehensive explanations based on complexity using many small effects. This article presents argument and empirical evidence that contemporary data analytic methods are problematic for all theory construction approaches. They are especially biased against web of causation approaches to theory construction. Mathematical arguments and new empirical evidence that supports web of causation explanations are presented.

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