Exploration of statistical dependence between illness parameters using the entropy correlation coefficient

Pharmacogenomics

Volumn 7, Issue 3, 2006, Pages 421-428

  Craddock, R Cameron ^a   Taylor, Renee ^b   Broderick, Gordon ^c   Whistler, Toni ^a   Klimas, Nancy ^d   Unger, Elizabeth R ^a  

^a CENTERS FOR DISEASE CONTROL AND PREVENTION   (United States)

^b UNIVERSITY OF ILLINOIS AT CHICAGO   (United States)

^c UNIVERSITY OF ALBERTA   (Canada)

^d UNIVERSITY OF MIAMI   (United States)

Author keywords

CFS; Entropy correlation coefficient; Fatigue; MFI; Mutual information

Indexed keywords

ARTICLE; BAYES THEOREM; CHRONIC FATIGUE SYNDROME; CORRELATION COEFFICIENT; DEPRESSION; FEMALE; HEALTH STATUS; HUMAN; MAJOR CLINICAL STUDY; PATHOGENESIS; RATING SCALE; SELF CONCEPT; SHORT FORM 36; STATISTICAL ANALYSIS; STATISTICAL MODEL; SYMPTOM; UNITED STATES;

ADULT; ALGORITHMS; BAYES THEOREM; CYTOKINES; DATA INTERPRETATION, STATISTICAL; DEPRESSION; ENTROPY; FATIGUE SYNDROME, CHRONIC; FEMALE; HUMANS; INTERLEUKIN-2; LINEAR MODELS; MODELS, STATISTICAL; NEUROPSYCHOLOGICAL TESTS; PSYCHIATRIC STATUS RATING SCALES;

EID: 33646038259     PISSN: 14622416     EISSN: 17448042     Source Type: Journal    
DOI: 10.2217/14622416.7.3.421     Document Type: Article

References (14)

1. Reyes M, Nisenbaum R, Hoaglin DC et al.: Prevalence and incidence of chronic fatigue syndrome in Wichita, Kansas. Arch. Intern. Med 163(13), 1530-1536 (2003),
2. Vernon SD, Reeves WC: The challenge of integrating disparate high-content data: epidemiological, clinical and laboratory data collected during an in-hospital study of chronic fatigue syndrome. Pharmacogenomics 7(3), 345-354 (2006).
3. Hill T, Lewicki P: STATISTICS. Methods and Applications. StatSoft, Tulsa, OK, USA (2006).
4. Shannon C: A mathematical theory of communication. Bell Systems Technical J. 27, 27-39 (1948).
5. Astola J, Virtanen I: A measure of overall statistical dependence based on the entropy concept. Proceedings of the University of Vaasa, Finland, Report No. 91 (1983).
6. Cover T, Thomas J: Elements of Information Theory. John Wiley & Sons, New York, NY, USA (1991).
7. Reeves W, Wagner D, Nisenbaum R et al: Chronic fatigue syndrome - a clinically empirical approach to its definition and study. BMC Med 3, 19 (2005).
8. Wagner D, Nisenbaum R, Heim C, Jones JF, Unger ER, Reeves WC: Psychometric properties of the CDC symptom inventory for assessment of chronic fatigue syndrome. Popul Health Mentr 3, 8 (2005).
9. Lavidor M, Weller A, Babkoff H: Multidimensional fatigue, somatic symptoms and depression. Br. J. Health Psychol 7(Pt 1), 67-75 (2002).
10. Robbins T, Sahakian B: Computer methods of assessment of cognitive function. In: Principles and practice geriatric psychiatry. Copeland J, Abou-Saleh M, Blazer D (Eds). John Wiley & Sons, Chichester, UK, 205-209 (1994).
11. Capuron L, Welberg L, Heim C et al: Cognitive dysfunction relates to subjective report of mental fatigue in patients with chronic fatigue syndrome. Neuropsychopharmacology (Epub ahead of print) (2005).
12. Jones JF, Nisenbaum. R, Reeves WC: Medication use by persons with chronic fatigue syndrome: results of a randomized telephone survey in Wichita, Kansas. Health Qual. Life Outcomes 1(1), 74 (2003).
13. Vernon SD, Unger ER, Dimulescu IM, Rajeevan M, Reeves WC: Utility of th e blood for gene expression profiling and biomarker discovery in chronic fatigue syndrome. Dis. Markers 18(4), 193-199 (2002).
14. Kullback S: Information theory and statistics. John Wiley & Sons, New York, NY, USA (1959)