Sem 2 (1) Flashcards
Classifications of statistics - define them
Descriptive (describing data)
Inferential (analysing data to enable conclusions to be drawn from data)
What is a statistic?
Collection, presentation, description and analysis of data which are measurable in numerical forms
Evidence based medicine definition
Conscientious, explicit and judicious use of current best evidence in making decisions about the care of individual patients
Integrating individual clinical expertise with the best available external clinical evidence from systematic research
Epidemiology
Study of distribution and determinants of health-related states or events in specified
populations and the application of this study to the control of health problems
Methods to carry out epidemiological studies
What are they used to study?
Surveillance and descriptive studies (distribution)
Analytical studies (determinants)
Surveillance and descriptive studies
How many groups?
Hypothesis?
How does it end?
One group
No explicit hypothesis
Development of possible hypothesis regarding cause and effect relationship
Analytical studies
How many groups?
Hypothesis?
How does it end?
two or more - for comparison
definite hypothesis regarding an exposure possibly causing an outcome
reject or accept hypothesis at end
What does a sample population require (3)
Representative
Unbiased - on target (dart board)
Precise - well grouped (dart board)
Larger studies
What are they?
What does this not equate to?
More precise
Does not equate to less bias
What are the two types of validity a study must have?
Internal
External
Internal validity
whether the study design, conduct, and analysis answer the research questions without bias
External validity
Degree to which conclusions/results can be applied to the population of interest
What does it mean if the study is internally valid?
the conclusions should be correct within the circumstances of the study
Types of error (2)
Chance - random
Bias - systematic
Chance error
What causes it?
How does it reduce?
Sampling variation (people selected)
As sampling size increases
Bias error
How is it quantified?
How is it effected if sample size increases?
the difference between the true value and expected value
Doesn’t reduce
What are the two types of bias error?
Selection bias
Information bias
Selection bias
What affects it? (3)
Study sample (external validity)
Group selection within a study (internal validity)
Healthy worker effect
External validity of selection bias
What is it
Study sample
Sample isn’t representative of the entire population of interest
Internal validity of selection bias
What is it
Group selection within a study
Groups within a study may not be comparable
Healthy worker effect
workers usually exhibit lower overall mortality than general population
Information bias
What affects it? (4)
Recall error
Observer/interviewer error
Measurement error
Misclassification
Recall error
What type of bias?
What is it?
Information
difference in recollection from study participants re event or experiences from the pass
Observer/interviewer error
What type of bias?
What is it?
Information
study observer or interview has preconceived expectations or knowledge that influences result
Misclassification error
What type of bias?
What is it?
Information
participants put in the wrong group e.g. diseased when aren’t
