Midterm #2 - Qualitative Research Design Flashcards
Main philosophical worldview that uses qualitative research designs
Post-positivism
What is Post-positivism?
Belief that there is 1 reality, 1 objective truth that is waiting to be discovered through research
Key defining features of post-positivism
DETERMINISM - Causes determine effects (use of experiments)
Reductionism = reduce ideas to small, discrete,
testable variables (makes hypotheses and
research questions)
Empirical observation and measurement = knowledge based on observation and measurement
Theory testing = theories are tested, supported, refined
Difference between Determinism and Causality
Determinism is a philosophical doctrine, and causality is a principle under it
Determinism
Doctrine that assumes every even has causes (nothing happens on it’s own)
- Makes a causal claim
- Post-positivist relation = we find and test for the cause
- no such thing as an “Accident”, implies no cause (injury prevention doesn’t like this, wants to anticipate and prevent)
Causality
Principle that everything has a cause
- Effects can have multiple causes
What do we need to claim causation?
1) Covariation
2) Isolation of causal variable
3) Effects come after causes (order)
4) Manipulating the cause will manipulate the effect
Covariation
Statistical correlation
correlation =/= causation !
Isolation of causal variable
Only x -> y. No z!
Cause is not because of a third variable
z a.k.a extraneous/control variable
3 Goals of Science
Describe - Descriptive (what) goals only cover CORRELATION
Explain - explanatory (how) goals
Predict - predictive (why) goals
- Both include causation
3 Types of claims
Causal (affects, leads to, causes, leads to, etc.)
Association (associated , relates, linked, correlates, etc.)
Frequency (counts, x # of, x% of, x-y/day, just giving the ‘what’, etc.)
Frequency claim
Describes rates or degrees of ONE measured variable
Association claim
At least 2 measured variables
- Correlated somehow (+, -, or 0)
- No manipulation or interference (takes away #4 of causal claim requirements)
- Make predictions based on strength of association (except for 0), stronger closer to 1
Causal claim
Variable x (expected to) changes variable y
- Independent and dependent variables
- Usually experimental design
Mediator variable
variable z that relates/bridges x and y
- Mediation model: X → Z → Y
- If you take Z away, no relationship
NOT the same as a “third variable”
- Interventions operate via mediators, so you NEED to identify it
Moderator variable
Changes sign/strength of the IV’s affect on DV
- Statistical interaction on a graph
- Effect modifiers = creates/enhances/modifies relationship
Confounder variable
Variable that changes relationship between IV and DV because it’s related to both
- Not part of the causal chain
- Source of difference for both variables (ex. population size in church-murder example)
Validity of qual. research designs is composed of
Internal and external validity
Validity of qual. measures are composed of
Content and statistical validity
Internal validity (IV)
Confidence in our results, and that any Δ in outcome was because of the treatment (also addressing threats to validity
- NOT because of a 3rd variable
Threats related to experimental procedure (IV)
Testing: participants just get better at the test, measures skill instead of their true reactions
Instrument Accuracy: Measures must be valid and reliable (working, no calibration error, no misuse, same collection technique)