Odds Ratio

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HBS108 (Measures of Association) Mind Map on Odds Ratio, created by shirley.ha on 10/09/2013.
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Mind Map by shirley.ha, updated more than 1 year ago
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Created by shirley.ha over 10 years ago
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Resource summary

Odds Ratio
  1. similar to RR but...
    1. 1. Is used mainly to analyse data from case-control studies.
      1. 2. Gives an approximation to the RR
        1. 3. Is used when RR is inappropriate (e.g., when examining rare diseases in the population using case-control designs).
          1. 4. Both OR and RR are also accompanied by confidence intervals.
          2. ratio of the odds of exposure among cases to the odds of exposure among the controls.
            1. why we use it?
              1. Because RR cannot be calculated in case-control studies, because these studies usually examine rare and uncommon diseases
                1. Unlike a cohort study, we do not know the risk for exposure in the population
                2. Interpretation
                  1. used to calculate risk from case-control studies but if the study is done well (that is, bias is limited as much as possible and the disease is rare),
                    1. valid measure of association that approximates the RR from a cohort study
                  2. the larger the OR, the stronger the association between the disease and the exposure
                    1. Confidence Intervals
                      1. provide information about the precision of the association.
                      2. CORRELATION CO-EFFICIENT (r)- Measures of assoc btwn the two variables
                        1. statistical measurement describing the degree and strength of the association between two continuous variables
                          1. Correlation rules
                            1. r=0
                              1. is no association between the variables
                              2. r=1
                                1. perfect +ve correlation, meaning that both variables move in the same direction together.
                                2. r=-1
                                  1. perfect -ve correlation, meaning that as one variable goes up, the other goes down
                                3. measures the degree to which values for two measures move together in a synchronised manner
                                  1. r closer 0- INDEPENDENT
                                    1. CLOSER TO ONE ANOTHER- DEPENDENT
                                  2. 2 ASPECTS
                                    1. Strength
                                      1. Direction
                                      2. correlation by itself does not imply causation
                                        1. correlations assess the strength of associations.
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