quantitate study design - critial numbers 1 Flashcards
what do descriptive statistics do
describe a sample
what do inferential statistics do
make inferences about our population
how can a sample be biased
when certain subgroups from the target population are over/under represented
it arises when imperfections in the research process cause our findings to deviate from the truth
what makes results generalisable
when the sample represents the population of interest
what does bias impact
the validity and reliability of study findings
what are the 5 types of bias
sampling bias
recall bias
information bias
the ‘hawthorne’ effect
attrition bias
define sampling bias
when the sample does not represent the population of interest
define recall bias
when there is inaccurate recall of past events/exposures/behaviours
define information bias
when there is incorrect measurement eg miscalibrated machine
define the ‘hawthorne’ effect
when participants change their behaviour when they know they are being observed
define attrition bias
when there is differential dropout from studies eg sicker participants drop out so our outcome is only measured on healthier participants
what are confounding variables
they obscure the real-life effect of exposure on an outcome
a confounder is related to both exposure and outcome
but is not on the causal pathway
what are the 2 types of study designs
experimental
observational
what is an experimental study design
when the researchers have intervened in some way
what is an observational study design
when the researchers have not intervened, and have merely observed
what are the 3 types of observational studies
retrospective - looking back into the past
cross-sectional - a single snapshot in time
prospective - following up over time
what are randomised controlled trials
when participants are randomly allocated to different interventions and follow up
