Lecture 6 - Chance, bias, confounding and true causal relationshiop Flashcards
What are measures of association?
- Identify causes of disease
- Estimate how much disease is due to an exposure
- Compare incidence of disease in two populations
- Common measures (relative risk, odds ratio, hazard ratio)
Relative Risk
ratio of the risk (incidence) of disease (the outcome) in those ‘exposed’ compared to the risk (incidence) of disease (the outcome) in those ‘not exposed’
RR = (incidence in exposed group)/(incidence in unexposed group)
What is the strongest study type in terms of evidence?
Meta-analysis of RCTs
What are two types of errors?
- Random Error
- Systematic Error (aka bias)
What is random error?
An error that decreases precision
What is systematic error?
An error that decreases validity
What are the three types of bias?
- Selection Bias
- Information Bias
- Confounding Factors
What is selection of bias?
Bias shown in selecting subjects
Usually results from comparative groups not coming from the same study base and not being representative of the populations they come from
What is information bias?
Bias shown in collecting information or measurements
What is the difference between chance and bias?
- Chance is caused by random error bias is caused by systematic error
- Errors from chance will dance each other out in the long run (w/ large sample size) bias won’t
- Chance leads to imprecise results while bias leads to inaccurate results
How do you asses the role of chance in a study?
- Hypothesis Testing
- Estimation
What is hypothesis testing?
- Use statistical test to examine the null hypothesis
- if p value is less than 0.05 then result is statistically significant
What is estimation?
- Uses statistical methods to estimate the range of values that is likely to include the true value
- It is associated with “confidence intervals” – if value corresponding to no effect falls outside interval then result is statistically significant
What are the benefits of Random Allocation (randomization)?
- Reduces bias in those selected for treatment (guarantees treatment assignment will not be based on patient’s prognosis)
- Prevents confounding (known and unknown potential confounders are evenly distributed)
What are the two conditions that must be met for confounding factors?
- Be associated with exposure (without being the consequence of exposure)
- Be associated with outcome (independently of exposure..not an intermediary)
How to minimize confounding factors?
Properly design a Randomized Control Trial to distribute confounding factors equally between the groups
What are the two main types of information bias?
- Reporting Bias (recall bias)
- Observer Bias (interviewer bias and biased follow-up)
What are Bradford Hill’s “Criteria” for Judging Causality?
- Temporality
- Consistency
- Strength of association
- Dose-response relationship
- Biological plausibility
- Specificity
- Experimental evidence
- Analogy
- Biological coherence
How is consistency good?
When all different evidences and studies etc show similar results
What does strong association mean?
It increases likelihood that relationship is one of cause and effect
What does a weaker association mean?
It means that it is difficult to exclude the alternative explanations (you need to take them seriously)
*But a weak association does not mean it is not causal
What is Dose-Response Relationship?
It illustrates that with increased dosage or decreased dosage a specific outcome is achieved
What is biological plausibility?
Biological mechanism by which exposure alters risk of disease
