Causal Inference, Bias, Confounding, Interaction Flashcards

1
Q

Describe two errors found in studies

A
  1. Random error
  2. Systematic error
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2
Q

Define a random error and an example

A

Inherent errors which fluctuate due to the unpredictablity or uncertainty in measuring process.

Measuring height affected by minor posture changes

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3
Q

Define systematic errors and give an example

A

Error that is predicatble and constant or proportional to the true value. Can be eliminated if identified

taring a balance

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4
Q

How can you minimse random errors?

A
  • Repeats
  • Lots of Data
  • Averages to recude errors
  • Statistically analyse
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5
Q

How can you reduce systematic errors

A
  • Careful design
  • Comparison of results to independent groups

Difficult to detect and correct

Cannot statistically analyse (as all values are ‘off’ in the same direction i.e. all too high or too low than true value)

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6
Q

Define Bias

A

Systematic errors in the design or conduct of study that results in incorrect estimate of association between exposure and ourcome

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7
Q

Describe the two main subtypes of bias

A

Selection Bias

Information Bias

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9
Q

Define selection bias

A

Results from selection of participants that is not representative of target population

  • If the right people don’t participate then the associations observed are not representative to the real world*
  • Systematic difference between the characteristics of those selected for the study and those who are not*
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10
Q

Give some examples of selection bias

A

Self-selection bias (volunteers)

Non-responder

Survival bias

Ending study early when outcomes have been achieved

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11
Q

Prevalence is influenced by _____ and _____ with disease; whilst incidence is influenced by _____ only.

A

Prevalence is influenced by exposure and survival with disease; whilst incidence is influenced by exposure only.

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12
Q

Define Survival bias

A

Bias that results from participants surviving the study period - can only be selected and analysed if they survive to study end point

Often seen in cross-sectional studies

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13
Q

Differentiate between point and period prevalence

A

Point: Prevalence of a disease at one point in time

Period: Prevalence of a disease over a period of time

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14
Q

What are some biases found in cohort studies

A

Self-selection: more likely to participate if have disease

Loss to follow up (20% max attrition)

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15
Q

Define Hazard Ratio

A

Hazard in the intervention group ÷ Hazard in the control group

Measure of an effect of an intervention on an outcome of interest over time.

Hazard ratio is reported most commonly in time-to-event analysis or survival analysis (i.e. when we are interested in knowing how long it takes for a particular event/outcome to occur).

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16
Q

How is a hazard ratio different to a Rsik or Odds ratio

A

Hazard ratio takes into account the total events and the time they occured

RR or OR only looks at the occurence of an event by the end of the study (i.e. ratio of whether or not an event occured:number of events)

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17
Q

Define causality

A

Measure of association between exposure and outcome

18
Q

Define a Confounder

A

A causal variable that affects the independent vairable and dependent variable

Is not on the causal pathway of exposure to outcome

19
Q

How can you reduce confounding (2)

A
  1. Design stage:
    1. randomisation
    2. Restriction
    3. Control matching
  2. Analysis Stage
    1. Stratification
    2. Standardisation
    3. Statistical modelling

IMPORTANT: to adjust for potential confounders, they must be measured

20
Q

Define Residual confounding

A

Distortion of values even after adjustment for confounders

May be influenced by study design

21
Q

What was the purpose of Bradford Hill’s nine criteria.

A

Provide epidemiological evidence of a causal relationship between a pressumed cause and an observed effect

22
Q

Name and briefly describe Bradfor Hill’s Criteria

A
  1. Strength - increased effect, likely causality
  2. Consistency - reproducible
  3. Specificity - specfic population at specific site with no other explanation
  4. Temporal - cause has to precede effect
  5. Biological Gradient - increase exposure, increase effect
  6. Plausibility - biological mechanism
  7. Coherence - agreement between epidemiological and laboratory evidence
  8. Experiment - RCT
  9. Analogy - similar facotrs causing same effect