Difference between revisions of "Measures of strength of association"
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| − | [[Analytic epidemiological studies|Analytic studies]] are conducted in an attempt to identify whether the disease experience in a population differs between groups of animals within this population (defined by exposure to 'risk factors' of interest), in the hope that some indication of a '''causal association''' can be achieved. Therefore, methods are required in order to quantify any 'evidence' in support of a possible association. Epidemiologists commonly measure this using '''measures of strength of association''' and through the use of '''[[Hypothesis testing|null hypothesis tests]]'''. | + | [[Analytic epidemiological studies|Analytic studies]] are conducted in an attempt to identify whether the disease experience in a population differs between groups of animals within this population (defined by exposure to 'risk factors' of interest), in the hope that some indication of a '''causal association''' can be achieved. Therefore, methods are required in order to quantify any 'evidence' in support of a possible association. Epidemiologists commonly measure this using '''measures of strength of association''' and through the use of '''[[Hypothesis testing|null hypothesis tests]]'''. It is important to use both of these measures whenever interpreting the results of an analytic study, as they measure different things. Measures of strength of association are an indication of the magnitude of the association, whereas the hypothesis test results give an indication of the probability of seeing the data obtained if there was no association between the exposure and outcome in the source population. |
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| + | ==Correlation coefficients== | ||
| + | Correlation coefficients are used when comparing two [[Quantitative data#Data types|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. | ||
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| + | ==Ratio measures== | ||
Revision as of 16:00, 4 May 2011
Analytic studies are conducted in an attempt to identify whether the disease experience in a population differs between groups of animals within this population (defined by exposure to 'risk factors' of interest), in the hope that some indication of a causal association can be achieved. Therefore, methods are required in order to quantify any 'evidence' in support of a possible association. Epidemiologists commonly measure this using measures of strength of association and through the use of null hypothesis tests. It is important to use both of these measures whenever interpreting the results of an analytic study, as they measure different things. Measures of strength of association are an indication of the magnitude of the association, whereas the hypothesis test results give an indication of the probability of seeing the data obtained if there was no association between the exposure and outcome in the source population.
Correlation coefficients
Correlation coefficients are used when comparing two 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.