Sampling Flashcards
Which has higher INTERNAL validity: randomized or non-randomized designs
Randomized - participants are randomly assigned to levels of the IV
Which has higher EXTERNAL and CONSTRUCT validity: randomized or non-randomized designs?
Non-randomized
Variance BETWEEN participants
Different groups have different conditions and the groups are compared to each other (use random assignment to assign participants to groups)
Variance WITHIN participants
Each participant experiences different conditions - participants as own comparison
Selection (threat to internal validity)
Pre-existing differences between participants in different experimental conditions. Occurs when there is no random assignment
Maturation (threat to internal validity)
Participants/things measured change over time (boredom, decay, growth, development, etc.) (e.g. measuring concentration in children, but older children concentrate better)
History (threat to internal validity)
Interruption from an unwanted source affects DV (e.g. room getting warmer during a concentration test, which affects concentration)
Test effects (threat to internal validity)
The observation changes what it observes (e.g. due to repetition, subjects learn to do a concentration test faster (i.e., memory is measured instead of concentration))
Instrumentation (threat to internal validity)
The observation is not done consistently - changes in measurement procedures/devices (e.g. measuring concentration and using a new concentration test on day two of experiment)
Mortality (threat to internal validity)
Drop out (e.g. participants do not return for the post-(treatment) test)
Selection by maturation (threat to internal validity)
Different groups mature differently (e.g. examining groups of adolescents according to birth-assigned sex; testing effect of protein intake on development of strength)
Simple random (probability sampling)
Every element has an equal and independent chance of selection
Probability sampling
Every element of a population has a known chance of being included in the sample
Stratified random sampling (probability sampling)
Population is divided into distinct strata based on specific criteria, then samples are drawn from each stratum separately and combined