Coleman, Stephen (2005): Testing Theories with Qualitative and Quantitative Predictions.

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Abstract
Researchers in the social sciences as well as other disciplines rely on statistical models to develop and test theories. The standard approach applies multivariate analysis—usually linear regression—and statistical hypothesis testing to observational data. The researcher may have several independent variables in mind as candidate predictors of the dependent variable; those reaching statistical significance compose the final model. In other situations, a theory is assumed to be correct and regression analysis is used to estimate parameters. Though experiments with random assignment of subjects are recognized as the “gold standard” for research, these are rarely possible in political science. Instead we rely on statistical controls to overcome problems inherent in using nonexperimental data.
This paper suggests that our confidence in using statistical methods to construct theories is misplaced and that theory testing is more productive when we combine definitive theorygenerated predictions with statistical methods. I begin with a review of problems in the current approach to statistical analysis, then give several examples of how prediction can be improved.
Item Type:  MPRA Paper 

Original Title:  Testing Theories with Qualitative and Quantitative Predictions 
Language:  English 
Keywords:  economic theory, theory testing, statistical testing 
Subjects:  B  History of Economic Thought, Methodology, and Heterodox Approaches > B4  Economic Methodology > B41  Economic Methodology C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C12  Hypothesis Testing: General C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C18  Methodological Issues: General 
Item ID:  105171 
Depositing User:  Dr Stephen Coleman 
Date Deposited:  15 Jan 2021 01:26 
Last Modified:  15 Jan 2021 01:26 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/105171 