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Measures of strength of association (view source)
Revision as of 16:12, 4 May 2011
, 16:12, 4 May 2011no edit summary
==Correlation coefficients==
==Correlation coefficients==
Correlation coefficients are used when comparing two [[Data types#Quantitative data|quantitative variables]], and are based upon the '''covariance''' between these variables amongst the individuals in the study population. The covariance can be viewed as how the two variables of interest differ in individuals in relation to their mean values in the whole population, but put more simply, is a measure of how two different variables change in relation ''to each other''. This value is standardised in order to give a correlation coefficient, which lies between -1 (indicating a perfect negative correlation) and +1 (indicating a perfect positive correlation), with a coefficient of 0 indicating no correlation.
Correlation coefficients are used when comparing two [[Data types#Quantitative data|quantitative variables]], and are based upon the '''covariance''' between these variables amongst the individuals in the study population. The covariance can be viewed as how the two variables of interest differ in individuals in relation to their mean values in the whole population, but put more simply, is a measure of how two different variables change in relation ''to each other''. As the magnitude of this variable will depend upon the magnitudes of the variables in question, this value is 'standardised' in order to give a correlation coefficient, which lies between -1 (indicating a perfect negative correlation) and +1 (indicating a perfect positive correlation), with a coefficient of 0 indicating no correlation. Therefore, correlation coefficients measure how closely associated the two variables of interest are to each other.
==Ratio measures==
==Ratio measures==
Although correlation coefficients are commonly used in statistical studies, epidemiological investigations often deal with binary exposures and outcomes (such as presence or absence of a proposed risk factor for disease, and presence or absence of disease itself). Therefore, '''ratio measures''' such as the '''prevalence ratio''', the '''risk ratio''', the '''rate ratio''' and the '''odds ratio''' are more commonly used as measures of strength of association in these studies.