NDLI: The Validity of the Neale and Kendler Model-Fitting Approach in Examining the Etiology of Comorbidity

Content Provider	Springer Nature Link
Author	Rhee, Soo Hyun Hewitt, John K. Lessem, Jeffrey M. Stallings, Michael C. Corley, Robin P. Neale, Michael C.
Copyright Year	2004
Abstract	Given that knowledge regarding the etiology of comorbidity between disorders can have a significant impact on research regarding the classification, treatment, and etiology of the disorders, the ability to reject incorrect hypotheses regarding the causes of comorbidity is very important. A simulation study was conducted to assess the validity of the Neale and Kendler (1995) model-fitting approach in examining the etiology of comorbidity between two disorders. First, data were simulated under the assumptions of the 13 alternative comorbidity models described by Neale and Kendler. Second, model-fitting analyses testing the comorbidity models were conducted on the simulated datasets. Thirteen sets of data with varying model parameters were simulated to test Neale and Kendler's assertion that their model-fitting approach is appropriate across a range of potential prevalences and degrees of familiality. The validity of the model-fitting approach in examining unselected twin data and a combination of selected family data and unselected family data was explored. The model-fitting approach successfully discriminated several classes of comorbidity models, although discrimination between models within classes of related models was less accurate. Results suggest that the model-fitting approach can be a useful tool in examining the etiology of the comorbidity between disorders if the caveats of the present study's results are considered carefully. As predicted by Neale and Kendler, variations in the disorder prevalences and familial correlations did not affect the validity of their model-fitting approach, but affected the power to discriminate the correct model. As suggested by Neale and Kendler, the model-fitting approach can be applied to both unselected and selected data and to both twin and family data.
Starting Page	251
Ending Page	265
Page Count	15
File Format	PDF
ISSN	00018244
Journal	Behavior Genetics
Volume Number	34
Issue Number	3
e-ISSN	15733297
Language	English
Publisher	Kluwer Academic Publishers-Plenum Publishers
Publisher Date	2004-01-01
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Human Genetics Neurosciences Evolutionary Biology
Content Type	Text
Resource Type	Article
Subject	Genetics Ecology, Evolution, Behavior and Systematics Genetics (clinical)

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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