Advanced statistics for testing assumed casual relationships : multiple regression analysis path analysis logistic regression analysis / Hooshang Nayebi.
2020
QA278
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Title
Advanced statistics for testing assumed casual relationships : multiple regression analysis path analysis logistic regression analysis / Hooshang Nayebi.
Author
ISBN
9783030547547 (electronic book)
303054754X (electronic book)
3030547531
9783030547530
303054754X (electronic book)
3030547531
9783030547530
Publication Details
Cham, Switzerland : Springer, 2020.
Language
English
Description
1 online resource
Item Number
10.1007/978-3-030-54754-7 doi
10.1007/978-3-030-54
10.1007/978-3-030-54
Call Number
QA278
Dewey Decimal Classification
519.5/35
Summary
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.
Bibliography, etc. Note
Includes bibliographical references and index.
Access Note
Access limited to authorized users.
Series
University of Tehran science and humanities series.
Available in Other Form
Print version: 9783030547530
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Table of Contents
1. Multiple Regression Analysis
2. Path Analysis
3. Logistic Regression Analysis.
2. Path Analysis
3. Logistic Regression Analysis.