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Advanced Statistics for Testing Assumed Causal Relationships

Multiple Regression Analysis Path Analysis Logistic Regression Analysis

  • Book
  • © 2020

Overview

  • Provides nontechnical descriptions 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

Part of the book series: University of Tehran Science and Humanities Series (UTSHS)

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Table of contents (4 chapters)

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About this book

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.

Authors and Affiliations

  • Department of Sociology, University of Tehran, Tehran, Iran

    Hooshang Nayebi

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