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January 1, 1984Academy of Management Review1,274 citations

Causal Analysis: Assumptions, Models, and Data

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CSChester A. SchriesheimLJLawrence R. JamesSMStanley A. Muliak

Key Points

  • The review aims to summarize the key concepts presented in the book on causal analysis.
  • Reviewed the book's content focusing on assumptions, models, and data relevance.
  • Analyzed the application of causal analysis techniques in different contexts.
  • Identified essential assumptions necessary for effective causal modeling.
  • Highlighted various models used in causal analysis and their practical applications.

Abstract

This article presents a review of the book “Causal Analysis: Assumptions, Models, and Data,” by Lawrence R. James, Stanley A. Mullak, and Jeanne M. Brett.

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Cite This Study

Schriesheim et al. (1984) studied this question.

synapsesocial.com/papers/6a0a108d30285ee4a1342c2chttps://doi.org/10.2307/258244
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