Empiricism and Theorizing in Epidemiology and Social Network Analysis
The connection between theory and data is an iterative one. In principle, each is informed by the other: data provide the basis for theory that in turn generates the need for new information. This circularity is reflected in the notion of abduction, a concept that focuses on the space between induct...
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| Format: | Article |
| Language: | English |
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Wiley
2011-01-01
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| Series: | Interdisciplinary Perspectives on Infectious Diseases |
| Online Access: | http://dx.doi.org/10.1155/2011/157194 |
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| _version_ | 1832561419329994752 |
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| author | Richard Rothenberg Elizabeth Costenbader |
| author_facet | Richard Rothenberg Elizabeth Costenbader |
| author_sort | Richard Rothenberg |
| collection | DOAJ |
| description | The connection between theory and data is an iterative one. In principle, each is informed by the other: data provide the basis for theory that in turn generates the need for new information. This circularity is reflected in the notion of abduction, a concept that focuses on the space between induction (generating theory from data) and deduction (testing theory with data). Einstein, in the 1920s, placed scientific creativity in that space. In the field of social network analysis, some remarkable theory has been developed, accompanied by sophisticated tools to develop, extend, and test the theory. At the same time, important empirical data have been generated that provide insight into transmission dynamics. Unfortunately, the connection between them is often tenuous and the iterative loop is frayed. This circumstance may arise both from data deficiencies and from the ease with which data can be created by simulation. But for whatever reason, theory and empirical data often occupy different orbits. Fortunately, the relationship, while frayed, is not broken, to which several recent analyses merging theory and extant data will attest. Their further rapprochement in the field of social network analysis could provide the field with a more creative approach to experimentation and inference. |
| format | Article |
| id | doaj-art-4203b07dd653408a956d8d34553d58d5 |
| institution | Kabale University |
| issn | 1687-708X 1687-7098 |
| language | English |
| publishDate | 2011-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Interdisciplinary Perspectives on Infectious Diseases |
| spelling | doaj-art-4203b07dd653408a956d8d34553d58d52025-02-03T01:25:06ZengWileyInterdisciplinary Perspectives on Infectious Diseases1687-708X1687-70982011-01-01201110.1155/2011/157194157194Empiricism and Theorizing in Epidemiology and Social Network AnalysisRichard Rothenberg0Elizabeth Costenbader1Institute of Public Health, Georgia State University, 140 Decatur Street, Atlanta, GA 30303, USAFamily Health International, Behavioral and Social Sciences Department, 2224 E NC Hwy 54, Durham, NC 27713, USAThe connection between theory and data is an iterative one. In principle, each is informed by the other: data provide the basis for theory that in turn generates the need for new information. This circularity is reflected in the notion of abduction, a concept that focuses on the space between induction (generating theory from data) and deduction (testing theory with data). Einstein, in the 1920s, placed scientific creativity in that space. In the field of social network analysis, some remarkable theory has been developed, accompanied by sophisticated tools to develop, extend, and test the theory. At the same time, important empirical data have been generated that provide insight into transmission dynamics. Unfortunately, the connection between them is often tenuous and the iterative loop is frayed. This circumstance may arise both from data deficiencies and from the ease with which data can be created by simulation. But for whatever reason, theory and empirical data often occupy different orbits. Fortunately, the relationship, while frayed, is not broken, to which several recent analyses merging theory and extant data will attest. Their further rapprochement in the field of social network analysis could provide the field with a more creative approach to experimentation and inference.http://dx.doi.org/10.1155/2011/157194 |
| spellingShingle | Richard Rothenberg Elizabeth Costenbader Empiricism and Theorizing in Epidemiology and Social Network Analysis Interdisciplinary Perspectives on Infectious Diseases |
| title | Empiricism and Theorizing in Epidemiology and Social Network Analysis |
| title_full | Empiricism and Theorizing in Epidemiology and Social Network Analysis |
| title_fullStr | Empiricism and Theorizing in Epidemiology and Social Network Analysis |
| title_full_unstemmed | Empiricism and Theorizing in Epidemiology and Social Network Analysis |
| title_short | Empiricism and Theorizing in Epidemiology and Social Network Analysis |
| title_sort | empiricism and theorizing in epidemiology and social network analysis |
| url | http://dx.doi.org/10.1155/2011/157194 |
| work_keys_str_mv | AT richardrothenberg empiricismandtheorizinginepidemiologyandsocialnetworkanalysis AT elizabethcostenbader empiricismandtheorizinginepidemiologyandsocialnetworkanalysis |