ch6 Flashcards
“The” experiment: terminology
Data collection method where one or more IVs are manipulated to measure the effect on the DV, and where you control for other causes
Ways to manipulate an IV
- Presence vs absence (e.g. bonus vs no bonus)
- Frequency (e.g. high bonus vs low, vs no bonus)
- Type (e.g. punishment vs reward)
Extraneous variable
Every possible variable that can influence the DV, other than the IV
•E.g. Store location, age, gender, culture..
The 2 main objectives of experimental studies
- To draw valid conclusions about the effects of IV(s) on DV (requires internal validity)
- To make valid generalisations towards a broader group/population (requires external validity)
Confound
A variable (Z) that threatens internal validity
To prevent confounds, include extraneous and control variables in the design
Lab experiment
Artificial setting to have as much control as possible over the manipulations (including online experiment)
Field experiment
Natural environment where manipulation is possible
- Problems with randomisation
- Problems to exclude external influences
Threats to internal validity: History effect
Events/factors outside the experiment have an impact on the DV during the experiment
Threats to internal validity: Maturation effect
Biological/physiological changes over time
Threats to internal validity: Testing effect
Prior testing affects the DV
Threats to internal validity: Instrumentation effect
The observed effect is due to a change in measurement
Threats to internal validity: Selection bias effect
Incorrect selection of respondents (experimental and/or control group)
Threats to internal validity: Mortality effect
Drop out of respondents during experiment
Threats to internal validity: Statistical regression effects
Extreme scores in the beginning and less extreme in the end, this is also called: regression to the mean
Illustration field study: One group pretest post test
e.g. you give all employees in a company a bonus, and you compare work motivation before bonus (t-1) with motivation after bonus (t)
O1 X O2
“Within participants”
Problems
•Possible changes in the company (e.g. MT) -> history effect
•Employees got more mature -> maturation effect
•Filling in the same questionnaire twice (01 and 02 can lead to) -> testing effects
Illustration field study: Static design
e.g. you split the group of employees within a company in 2, give one group a bonus and the other group no bonus. You compare work motivation of the treatment group with work motivation of the control group.
G1: X 01
G2: 02
“Between participants”
Problems:
•Possible (demographic) differences between groups might explain the effects -> selection bias effect
•Participants in the control group may be frustrated and leave the company -> mortality effect
Increasing internal validity: controlling for extraneous variables
- Randomization: random allocation of participants to different conditions (selection bias, but also instrumentation, history, mortality) *difficult to control in the field
- Design control
- Control group: include group that does NOT receive the treatment (history, and maturation, but also instrumentation and statistical regression)
- Extra groups: groups without pre-test, but with an experimental manipulation (to exclude the effects of pre-testing) (testing)
•Statistical control: measure extraneous variables, and include theses in the statistical analysis (covariance analysis) (history and selection bias)
Illustration lab study: True lab experiment
E.g. You randomly allocate participants to conditions, ask them to work on a task, and make sure that the only thing that is different between groups is the fact that you give a bonus to group 1 and no bonus to group 2.
G1: R X 01
G2: R 02
“Between participants”
Problems:
•External validity
•In many cases it is wise to start research with an internally valid lab experiment and let it be followed by an externally valid real life field experiment
