Chapter 13 Quasi-Experiments

Question 1

how are quasi-experiments similar to experiments?

Answer 1

has IVs and DVs

Question 2

main difference between quasi experiments vs experiments

Answer 2

quasi experiments don’t have full experimental control and don’t use random assignment

Question 3

when are quasi experiments typically used?

Answer 3

in situations where random assignment is unethical (real world situations that can’t be manipulated)

Question 4

what does the term “nonequivalent” refer to in quasi designs?

Answer 4

no use of random assignment

Question 5

types of quasi designs

Answer 5

nonequivalent control group posttest only
nonequivalent control group pretest/posttest
nonequivalent control group interrupted time series

Question 6

2 main characteristics of a nonequivalent control group design

Answer 6

1. no use of random assignment; instead participants were either all born with something, exposed to something naturally occurring, etc.
2. at least 1 treatment group and 1 comparison group

Question 7

what comparisons do we want to make in nonequiv posttest only designs?

Answer 7

between-subjects

Question 8

which threat is heavy in nonequiv posttest only design?

Answer 8

selection threats

Question 9

nonequivalent pre/post design controls most threats to internal validity except for?

Answer 9

selection effects

Question 10

when is the DV measured in interrupted time-series design?

Answer 10

repeatedly (before, during (could be several times) and after)

Question 11

3 pros to interrupted times series design

Answer 11

-results are interpretable
-cam see normal fluctuation and trends
-can see how long lasting an effect is

Question 12

why is an interrupted time series design better than a 1 group pre/post design?

Answer 12

there’s more data points which makes it easier to interpret

Question 13

how many groups does an interrupted time-series design have?

Answer 13

2 or more

Question 14

does the timing of the interruption differ b/w groups in interrupted-time series designs?

Answer 14

yes

Question 15

which effects are found in quasi-experiments

Answer 15

selection effects; we don’t know if the change in DV is due to the IV or a shared participant characteristic

Question 16

solutions to eliminating selection fx in quasi experiments

Answer 16

1. create matched groups
2. waitlist: upgrade the quasi to a true experiment

Question 17

threats found in quasi experiments

Answer 17

design confounds
maturation threat
history threats
regression to the mean
attrition
testing and instrumentation threats
observer bias
demand characteristics
placebo fx

Question 18

maturation threats are typical in which designs

Answer 18

pretest-posttest

Question 19

which threats can be addressed by adding a comparison group in quasi experiments

Answer 19

maturation
history
testing

Question 20

how to control for observer bias in quasi experiments

Answer 20

use a masked or double blind design

Question 21

pros of carefully designed quasi experiments

Answer 21

-provides real-world data (not simulated experiments)
-typically high external validity
-allows us to study issues that cannot be ethically studied in experiments
-high construct validity of the IV

Question 22

similarities b/w quasi and correlational designs

Answer 22

-no random assignment
-both prone to internal validity threats

Question 23

key differences b/w quasi and correlational designs

Answer 23

-in quasi: we actively seek out naturally occurring comparison groups
-quasi is more meaningful/closer to establishing causation

Question 24

small N vs large N designs

Answer 24

small N: limited number of participants, high amount of data for each participant
large N: high number of participants, their data gets averaged out and we learn less about each person typically

Question 25

adv and disadv for small N designs

Answer 25

adv: studies special cases, can have some experimental control if compared to matched control groups disadv: external validity, internal validity sometimes

Question 26

small N designs are commonly used in which field of psychology and why?

Answer 26

therapy/behavior analysis, because it allows for modifying the behaviors of certain individuals to produce a desired result

Question 27

3 small N designs

Answer 27

stable-baseline multiple-baseline reversal

Question 28

stable-baseline design

Answer 28

an extended observation of baseline before intervention is introduced

Question 29

when do we know a stable-baseline design was effective

Answer 29

if the target behavior changes only after intervention

Question 30

what threats can stable-baseline designs rule out

Answer 30

maturation regression to the mean

Question 31

multiple baseline design

Answer 31

staggers interventions across times, settings, or situations

Question 32

reversal designs

Answer 32

target behavior improves during treatment but reverses to baseline when treatment is removed

Question 33

when are reversal designs used

Answer 33

when treatment does not have a long term effect

Question 34

discuss 4 big validities for small N designs

Answer 34

internal: can be high if the study was carefully designed external: can be problematic depending on the goals of the study construct: can also be high if definitions and observations are precise statistical: not always relevant to small N studies bc we're looking at a limited number of participants