Relationship Relation: Association: real and spurious Statistical:

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Presentation transcript:

Relationship Relation: Association: real and spurious Statistical: Correlation: harmonic Causation

Causation: -direct factor outcome -indirect factor outcome Types of causal relationship: 1- factor is necessary and sufficient (rare), ex.; agent host A outcome

2- factor is necessary but not sufficient: A+B+C outcome 3-factor is not necessary but sufficient: A B C outcome or or

4- neither necessary nor sufficient: A + B + C D + E + F outcome or

A B A + B C A B + C A B C A B A B C C

Systematic error (bias) Confounders Before starting to prove causation, We should Identify and evaluate the effects of: Random Error (chance) Systematic error (bias) Confounders

Conditions for a relationship to be causal: 1- Strength of the association 2- Temporal relationship 3- Dose response relationship 4- Replication of results 5- Biological plausibility

Others: 1- Specificity 2- Consistency 3- Presence of alternative hypothesis 4- Cessation of exposure