Critical Numbers Flashcards
Sampling
We take a representative sample from the population of interst
We describe our sample using descriptive statistics
We make inference about our population using inferential statistics
Samples may be randomly or non-randomly selected
There are different methods of random and non-random sampling
Important thing is sample must represent population of interest
This helps make our results generalisable
When certain subgroups from the target population are over/under-represented the sample may be biased
e.g. GP survey which excludes centres in lower socioeconomic status areas
Bias
Bias’ arises when imperfections in the research process cause our findings to deviate from the truth
Bias can occur in all studies
It can occur intentionally or unintentionally
It impacts upon the validity and reliability of study findings
Put simply, it can distort results
It is our responsibility to minimise bias in our research
and consider it when critically evaluating the research of others
Types of bias
Sampling bias
Recall bias
Information bias
The ‘Hawthorne’ effect
Attrition bias
Sampling bias
sample does not represent population of interest
Recall bias
inaccurate recall of past events/exposures/behaviours
Information bias
incorrect measurement e.g. miscalibrated machine
The ‘Hawthorne’ effect
participants change their behaviour when they know they are being observed
Attrition bias
differential dropout from studies e.g. sicker participants drop out so our outcome is only measured on healthier participants
Cofounding
Confounding, if unaccounted for, is a form of bias
Confounding variables obscure the real effect of an exposure on an outcome
They may suggest that there is a relationship between two factors when there isn’t actually, or vice versa
What is a cofounder?
A cofounder is related to both exposure and outcome
But is not on the casual pathway
E.g a high salt diet can cause high blood pressure which can lead to stroke. So blood pressure is NOT a cofounding factor in the relationship between deit and stroke, rather than a mechanism
Correlation does not imply causation
Potential cofounders must be considered in the design, analysis and interpretation of studies
Studies can be classified according to whether they are:
Experimental – the researchers have intervened in some way
Observational – the researchers have not intervened, merely observed
Observational studies can be:
Retrospective – looking back into the past
Cross-sectional – a single snapshot in time
Prospective – following up over time
Randomised controlled trials
Randomly allocate participants to different interventions and follow up
Experimental
Prospective
Slide 23
There are variations on the standard RCT design
Cluster randomised trails
Crossover trials
Multi-arm and factorial trials
Adaptive design trials
Regardless of design, all clinical trials are monitored throughout to ensure participant safety and integrity of results.
