Observational research methods

Objective	Common design
Prevalence	Cross sectional
Incidence	Cohort
Cause (in order of reliability)	Cohort, case-control, cross sectional
Prognosis	Cohort
Treatment effect	Controlled trial

 

Cohort studies

• Cohort studies describe incidence or natural history.
• They analyse predictors (risk factors) thereby enabling calculation of relative risk.
• Cohort studies measure events in temporal sequence thereby distinguishing causes from effects.
• Retrospective cohorts where available are cheaper and quicker.
• Confounding variables are the major problem in analysing cohort studies.
• Subject selection and loss to follow up is a major potential cause of bias.

Study design for cohort studies

Cohort studies look forwards in time by following up each subject

• Subjects are selected before the outcome of interest is observed
• They establish the sequence of events
• Numerous outcomes can be studied
• They are the best way to establish the incidence of a disease
• They are a good way to determine causes of diseases
• The principal summary statistic of cohort studies is the relative risk ratio 
• If prospective, they are expensive and often take a long time for sufficient outcome events to occur to produce meaningful results 

 

Cross sectional studies

• Cross sectional studies are the best way to determine prevalence
• Are relatively quick
• Can study multiple outcomes
• Do not themselves differentiate between cause and effect or the sequence of events

Study design for cross sectional studies

Cross sectional studies look at each subject at one point in time only

• Subjects are selected without regard to the outcome of interest
• Less expensive
• They are the best way to determine prevalence
• Quick
• The principal summary statistic of cross sectional studies is the odds ratio
• Weaker evidence of causality than cohort studies
• Inaccurate when studying rare conditions 

 

Case-control studies

• Case-control studies are simple to organise
• Retrospectively compare two groups
• Aim to identify predictors of an outcome
• Permit assessment of the influence of predictors on outcome via calculation of an odds ratio
• Useful for hypothesis generation
• Can only look at one outcome
• Bias is an major problem

Study design for case-control studies

Case-ontrol studies look back at what has happened to each subject 

• Subjects are selected specifically on the basis of the outcome of interest
• Cheap
• Efficient (small sample sizes)
• Produce odds ratios that approximate to relative risks for each variable studied
• Prone to sampling bias and retrospective analysis bias
• Only one outcome is studied 

 

  ref.  Emerg Med J 2003;20:54-60