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Advanced Statistics for Testing Assumed Causal Relationships
(Englisch)
Multiple Regression Analysis Path Analysis Logistic Regression Analysis
Nayebi, Hooshang

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Advanced Statistics for Testing Assumed Causal Relationships

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  • Springer Basel AG
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  • 491259038

Produktbeschreibung

It presents that potential effects of each independent variable on the dependent variable are not limited to direct and indirect effects. The path analysis shows each independent variable has a pure effect on the dependent variable. So, it can be shown the unique contribution of each independent variable to the variation of the dependent variable.

This book concentrates on linear regression, path analysis and logistic regressions, the most used statistical techniques for the test of causal relationships. Its emphasis is on the conceptions and applications of the techniques by using simple examples without requesting any mathematical knowledge. It shows multiple regression analysis accurately reconstructs the causal relationships between phenomena. So, it can be used to test the hypotheses about causal relationships between variables. It presents that potential effects of each independent variable on the dependent variable are not limited to direct and indirect effects. The path analysis shows each independent variable has a pure effect on the dependent variable. So, it can be shown the unique contribution of each independent variable to the variation of the dependent variable. It is an advanced statistical text for the graduate students in social and behavior sciences. It also serves as a reference for professionals and researchers.


1.  Multiple Regression Analysis.- 2. Path Analysis.- 3. Logistic Regression Analysis.


Inhaltsverzeichnis



1. Multiple Regression Analysis.- 2. Path Analysis.- 3. Logistic Regression Analysis.


Klappentext

This book concentrates on linear regression, path analysis and logistic regressions, the most used statistical techniques for the test of causal relationships. Its emphasis is on the conceptions and applications of the techniques by using simple examples without requesting any mathematical knowledge. It shows multiple regression analysis accurately reconstructs the causal relationships between phenomena. So, it can be used to test the hypotheses about causal relationships between variables. It presents that potential effects of each independent variable on the dependent variable are not limited to direct and indirect effects. The path analysis shows each independent variable has a pure effect on the dependent variable. So, it can be shown the unique contribution of each independent variable to the variation of the dependent variable. It is an advanced statistical text for the graduate students in social and behavior sciences. It also serves as a reference for professionals and researchers.




Provides nontechnical deillegalscriptions that help the reader to learn quickly

Includes twenty-one examples on test of the causal relationships that help the reader to understand applications well

Presents innovative explanations of the various effects of variables, raw, direct, indirect, spurious, and pure



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