W8 Flashcards
Advantages of experiments
- allow to determine which variables have an authentically causal design
- identify variables that have significant causal relationships
- identify variables that have no significant effect on other variable
Disadvantages of experiments
- artificiality of experimental conditions (lab setting - not real life scenario) –> lack of ecological isomorphism
- more sophisticated designs may require large number of people who are willing to become experimental participants, maybe for extended periods of time
Lack of ecological isomorphism
conditions in lab as not the same as the ones in the outside world, meaning the study is not as replicable
Ex-post facto designs
no manipulation of the IV, but still the relationship between variables and potential causes are studied
research analyzes the effects of an IV that has occurred naturally (e.g. gender, level of education) on a DV (e.g. academic performance, communication style)
Field experiments
expose participants to different conditions to compare the effects of the manipulation on the IV (diff conditions)
e.g.
condition 1: studying in a group
condition 2: studying individually
observation: test performance
Ex-post facto vs field experiments
ex-post facto designs and field experiments may not be as reliable as the researcher has no idea how individuals in the two groups differ outside of the conditions they were assigned to
it may be that some other circumstance other than their condition explains the difference in results.
Basic experimental design
x= manipulation of variable (conditions)
r = random assignment of individuals to groups
O1 O2 etc = observation 1, observation 2, etc.
One group pretest-posttest design
O1 X O2
to be certain that a causal relationship is found rule out two possibilities:
1) O2 may have occurred anyway for some reason (snot necessarily due to O1)
2) some influence other than the study conditions caused the change
rule out all other possible explanations before deciding that only the study conditions are explaining the difference in the observations
Designing for control
CV - not exposed to any change
control - remove all possible variables from experimental design to ensure only the IV is causing the changes
Two group pretest-posttest design
O1 X O2
O1. O2
both groups are measured before and after one group experiences an experimental condition, the other group is the control group
Designing for random assignment
allows to assume the probability of something occurring in one group is no greater or less than the probability of it occurring in another group
Random assignment for 2 group pretest-posttest design
R O1 X O2
R O1. O2
Solomon four-group design
1) compare pretest with posttest
2) compare control groups with experimental groups
3) also takes a look at a group to which nothing has happened except for a final test
Factorial designs
analysis that examine the relationship among 3 or more variables - multivariate analysis
experimental designs that manipulate two or more variables - factorial designs
Between subjects design
diff groups of participants are exposed to different conditions or levels of the IV, each participant experiences only one condition
Within subjects design
same participants are exposed to all conditions of the IV, every participant experiences every level or treatment
Time series analysis
when we cannot know if the results obtained at the end of the experiment will still be true at some point in the future, problem
Internal validity - spurious relationship
not a genuine relationship between two variables but one that only seems to exist
