@article {1522,
	title = {Analytical and biologic variability in measures of hemostasis, fibrinolysis, and inflammation: assessment and implications for epidemiology.},
	journal = {Am J Epidemiol},
	volume = {149},
	year = {1999},
	month = {1999 Feb 01},
	pages = {261-7},
	abstract = {<p>An increasing number of cardiovascular epidemiologic studies are measuring non-traditional risk markers of disease, most of which do not have established biovariability characteristics. When biovariability data have been reported, they usually represent a short time period, and, in any case, there is little consensus on how the information should be used. The authors performed a long-term (6-month) repeated measures study on 26 healthy individuals, and, using a nested analysis of variance (ANOVA) approach, report on the analytical (CVA), intraindividual (CVI), and between individual (CVG) variability of 12 procoagulant, fibrinolysis, and inflammation assays, including total cholesterol for comparison. The results suggest acceptable analytical variability (CVA < or = 1/2 CVI) for all assays. However, there was a large range of intraindividual variation as a proportion of total variance (2-78\%), and adjusting for intraindividual and between individual variation in bivariate correlations increased the observed correlation by more than 30 percent for three of these assays. Overall, the assays showed a significant increase in intraindividual variation over 6 months (p < 0.05). While these findings suggest that most of these assays have biovariability characteristics similar to cholesterol, there is variation among assays. Some assays may be better suited to epidemiologic studies, and knowledge of an assay{\textquoteright}s biovariability data may be useful in interpreting simple statistics, and in designing multivariate models.</p>},
	keywords = {Adult, Aged, Analysis of Variance, Cardiovascular Diseases, Cholesterol, Epidemiology, Female, Fibrinolysis, Hemostasis, Humans, Inflammation, Male, Middle Aged, Models, Statistical, Multivariate Analysis, Risk Factors},
	issn = {0002-9262},
	author = {Sakkinen, P A and Macy, E M and Callas, P W and Cornell, E S and Hayes, T E and Kuller, L H and Tracy, R P}
}
