Cross-Sectional Studies Flashcards
Definition of Cross-Sectional Studies
- Observational studies that capture health/disease and exposure status at the same time.
AKA Prevalence study
Why are cross-sectional studies so named?
Because information gathered represents what is occurring at a point in time or time-frame across a large population.
Acquired without regard to exposure or disease/outcome status
Who is selected for a cross-sectional study?
Entire population or a subset
What does a cross-sectional study focus on?
- focuses simultaneously on disease & population characteristics, including exposures, health status,…
- Seeks associations
- Generates and tests hypotheses
- by repetition in different time periods
What are the two cross-sectional approaches?
- Collect data on each member of the population
- Take a sample of the population & draw inferences to the remainder
What is a probability sample?
Every element in the population has a known probability of being included in sample
What are some examples of probability sampling schemes?
- Simple Random sampling
- Systematic Random sampling
- Stratified Simple Random sampling
- Stratified Disproportionate Random sampling
- Multi-Stage Random sampling
- Cluster Multi-Stage Random sampling
Simple Random Sampling
- Assign random sampling, then take randomly-selected number to get desired sample size
- Assign random numbers, then sequentially-list numbers and take desired sample size from top of numbers
Systemic Random Sampling
- Assign random numbers, then randomly sort the numbers, select the 1st or last number and then every Nth number from there
Stratified Simple Random Sampling
Stratify by desired characteristic, then use Simple Random sampling to select desired sample size
Stratified Disproportionate Random Sampling
- disproportionately utilizes stratified sample when baseline population is not at the desired proportional percentage to the referent population
- stratified sample ‘weighted’ to return sample population back to baseline pop
Multistage Random Sampling
Uses simple random sampling at multiple staged towards patient selection
Cluster Multistage Random Sampling
Same as multistage random sampling but all elements clustered together or selected for inclusion
Non-probability sampling schemes
- Quasis-systematic or Convenience samples
Quasi-Systematic or Convenience samples
Decide on what fraction of population is to be samples and how they will be sampled.
Eg. All persons with last name A-H