Lecture 7: General Methodologies Of Study Design Flashcards
Two types of quantitative studies
Interventional and observational
What occurs in an interventional study?
Researchers forces people into groups— typically by a type of randomization
Leads to increasing evidence and hopefully causation
What’s the basis of observational studies?
“Natural” study— people are NOT forced into groups.
Useful for when group allocation is unethical.
What is a weakness of observational studies?
Most are not able to prove causation
How do you decide which type of study to use?
It all depends on the RESEARCH QUESTION that you are trying to answer.
How are subjects chosen for certain studies?
Depends on: Research question Population of interest Inclusion/exclusion criteria Case/control OR exposed/unexposed groups
How does selection criteria impact a study?
Selection criteria is inclusion/exclusion criteria. It affects generalizability and external validity
EX: mental health exchangeability
Types of Null hypotheses
Superiority
Non-inferiority
Equivalency
Superiority question/null hypothesis
Question: is my drug SUPERIOR to placebo/another drug?
Null hypothesis: drug is NOT superior to placebo/another drug
Non-inferiority question/null hypothesis
Question: is my drug NOT WORSE than another drug?
Null hypothesis: drug IS worse than other drug
Equivalency question/null hypothesis
Question: is my drug equal to other drug?
Null Hypothesis: drug is NOT equal to other drug
What are the different types of sampling/randomization?
Simple random Systematic random Stratified simple random Stratified disproportionate random Multi-stage random Cluster multi-stage random Quasi-systematic
Simple random
Assigned numbers then randomly pick numbers
Systematic random
Assign random numbers and then randomly sort the numbers, then systematically choose desired sample
Ex: top 10, bottom 10, every 3rd, etc.
Stratified simple random
Framed by desired characteristic, then use simple random to select desired sample size
Ex: stratified by gender
Stratified disproportionate random
Disproportionately uses stratified simple random sampling when baseline pop is not as desired proportional percentages to the referent population
“Weighted” to return to baseline
Useful for over-sampling
Ex: adding/removing based on race to mimic USA population