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NCJ Number: 119491 Find in a Library
Title: Testing Causal Hypotheses About Correlated Trends: Pitfalls and Remedies
Journal: Contemporary Drug Problems  Volume:15  Issue:4  Dated:(Winter 1988)  Pages:565-606
Author(s): O J Skog
Date Published: 1988
Page Count: 42
Type: Report (Study/Research)
Format: Article
Language: English
Country: United States of America
Annotation: This essay points out that when alcohol and drug-related data are used to test hypotheses about causal relationships among phenomena varying in time, researchers must carefully control for the presence of trends in the data. Failure to do so may cause relationships between variables to be exaggerated, deflated or even inverted.
Abstract: Those carrying out sociological and epidemiological research often explain changes in one phenomenon in terms of changes in another phenomenon on the basis of comparison of trends. These explanations can be misleading, for two series may coincide even though there is no causal relationship between the two phenomena. On the other hand, two trends may be uncorrelated or divergent even though there is a positive and significant causal relationship between the two phenomena. Such anomalies occur frequently and it is important to distinguish apparent from sound evidence. The article asserts that a simple operation called filtering can solve some of these problems and outlines a statistical strategy for its use. 29 references.
Main Term(s): Correlation analysis
Index Term(s): Drug effects; Research methods; Statistics
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