Abstract
Objectives: This paper aims to develop and describe a method for combining, comparing, and maximizing the statistical power of two longitudinal studies of risk factors for cardiovascular disease that did not have identical data collection methodologies.
Methods: Subjects from a 1986 cross-sectional study (n= 180) were pair-matched with subjects of corresponding gender and age (+ 5 years) from a 1990 cross-sectional study. The methodology is described and results are calculated for various measures of cardiovascular risk or risk factors (e.g. cholesterol, Finnish Risk Score).
Results: Box's test of equality and symmetry of covariance matrices gave chi-square values of 223.8 and 710.0 for two cardiovascular risk factors (cholesterol and cardiac risk score, respectively); these values were highly significant (p=0.0001). For the North Karelia Risk Score, repeated measures ANOVA revealed a borderline significant interaction for treatment by time (p=0.054) and a significant interaction for treatment by time by country (p=0.035). These probabilities compared favorably with a randomized blocks model.
Conclusions: Creation of a synthetic longitudinal control group resulted in a statistically valid ANOVA model that increased the statistical power of the study.
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