Article

The Norsjö-Cooperstown healthy heart project: a case study combining data from different studies without the use of meta-analysis.

The Mary Imogene Bassett Research Institute, Cooperstown, New York 13326-1394, USA.
Scandinavian journal of public health. Supplement (impact factor: 1.44). 02/2001; 56:40-5. pp.40-5
Source: PubMed

ABSTRACT 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.
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).
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.
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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Keywords

1990 cross-sectional study
 
borderline significant interaction
 
cardiac risk score
 
cardiovascular disease
 
cardiovascular risk
 
cardiovascular risk factors
 
chi-square values
 
corresponding gender
 
covariance matrices
 
Finnish Risk Score
 
longitudinal studies
 
measures ANOVA
 
North Karelia Risk Score
 
randomized blocks model
 
risk factors
 
significant interaction
 
statistical power
 
statistically valid ANOVA model
 
synthetic longitudinal control group
 
various measures