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Kenny Dyadic Data Analysis

David A. Kenny, PhD, is a Professor of Psychology and the author of a number of books and articles dealing with interpersonal perception, mediational analysis, and inspection of social interaction data. One area that holds his interest is dyadic data analysis. This particular form of statistical analysis as well as bivariate data analysis also possibility of revealing answers to questions about various interpersonal phenomena.

statistical data analysis schema

What is Dyadic Data Analysis?

It centers on pairs of people, or dyads. These interact socially and share a very close relationship such as being roommates, or married couples. It is also possible given the teamwork orientation of modern business for coworkers to be dyads. The important consideration is that in reviewing the dyads performing separate analysis for each person is going to cause problems in the final interpretation. A dyadic analysis requires that data from all members of the dyad be together in one observation, using the same set of variables. The dyad itself is important and there is no independence between members in the dyad.

An example would be doing an analysis of a family where one person is suffering from a psychological problem. Each is a member of the dyad and interacts on a constant basis. Trying to determine what each family member does to affect psychological problem ignores the more critical influence of the dyad. The analysis must take a look at all the information of the group because of that. Regression analysis and factor analysis are two statistical tools that can be used rather well in this type of work. More complex analysis that can be obtained through SEM or MLM techniques can help draw further information from dyadic data analysis efforts.

Kenny Sponsors Dyadic Data Analysis Workshops

Dyadic data analysis allows for a better understanding of how pairs and groups impact on each other. Simply looking at one person at a time means that the interplay is not given the importance is due. Researchers are encouraged to take a close look at dyadic data analysis, and determine how it can provide positive results for research. Dr. Kenny will sponsor workshops on dyadic analysis for their continued education.

Non-independence is an important concept that has to be understood for effective dyadic data analysis. This is something that Dr. Kenny covers in the work. Dyadic analysis can include investigation information over a period of time, and its effects can be mediated or moderated. The dyadic data analysis workshops include discussion of the various physical software packages such as SPSS that are used in interpreting the data, and structural equation modeling is topical area.

Dyadic Analysis Has Corporate Value

While this does have current importance in areas of psychology and behavioral abnormalities, there is an area where dyadic data analysis can provide a major benefit: organizational behavior in a corporate setting. As alluded to earlier, corporations are now relying increasingly more on teamwork as a means of production. Employees work closely in teams for forty or more hours a week. Understanding the internal dynamics is extremely important.

The analysis of Dr. Kenny is using may allow corporate management better understanding of interaction of people working on the same project. The result can arguably be greater workforce efficiency!