The Norsjö-Cooperstown healthy heart project: A case study combining data from different studies without the use of meta-analysis
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TL;DR
creation of a synthetic longitudinal control group resulted in a statistically valid ANOVA model that increased the statistical power of the study.
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.
