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Causal Relationships in Population Analysis

  • Shiva S. Halli
  • K. Vaninadha Rao
Part of the The Plenum Series on Demographic Methods and Population Analysis book series (PSDE)

Abstract

Demographers are concerned with the interrelationships between population and society. Hence, a major function of population studies has been not only the collection and dissemination of relevant facts regarding populations, but also the understanding of these population—society interrelationships. The relationships described above are of two types: descriptive and causal. While empirical research easily accommodates the description of relevant associations, cause-and-effect relationships are often difficult to isolate. For example, although different populations can be described in terms of recognized criteria, particular patterns and processes can only be understood in terms of a general conception of the interrelationships between variables as applied to a particular context. Research questions suggest the existence of these causal relationships, but the appropriate statistical methods are determined by the proposed answer to the research question. Multivariate statistical techniques provide the precision often required to respond to specific research needs, particularly when dealing with applied research. They have given population specialists the ability to probe more deeply than ever before into the details of causal interrelationships.

Keywords

Path Analysis Population Analysis Path Coefficient Sample Correlation Matrix Implicit Variable 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© Springer Science+Business Media New York 1992

Authors and Affiliations

  • Shiva S. Halli
    • 1
  • K. Vaninadha Rao
    • 2
  1. 1.University of ManitobaWinnipegCanada
  2. 2.Bowling Green State UniversityBowling GreenUSA

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