Download Experimental Design (7)

Experimental Design (7)
Kerry Kilborn
Department of Psychology
Overview
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•
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Confounding variables
Experiment vs. Correlational Study
Between-Subjects Design
Equivalent Groups
Quasi-Experiments
Summary
Experimental Studies
Manipulation of IV
Change in DV
causal link
Alcohol level
Reaction Time
Memory load
Recall Rate
Drug/Placebo
Pain Score
Alcohol
50
No Alcohol
Reaction Time [ms]
Sample
(N = 100)
50
375
350
325
300
0
No
Yes
Alcohol
Confounding Variables
Confounding
IV
Reaction Time
Testing Time
No Alcohol
325 ms
10 am
Alcohol
366 ms
10 pm
Confounding Variables
Possible Confounding Variables
Person-specific
Situation-specific
– Age
Experimenter
– Education
Time point of testing
– Socio-economic status
Testing environment
– Motivation
Apparatus
– Memory
Stimulus intensity
– Intelligence
Duration
Experimental Studies
• what happens in an Experiment:
• Manipulation of independent variables (IVs)
• Control of confounding (extraneous) variables
• Measurement of dependent variables (DVs)
Experiments - Evaluated
Strength
Weakness
isolates cause and effect
participant bias
control of extraneous variables
→ high internal validity
artificial conditions and
measures
→ (low) external validity
elimination of alternative
explanations
participants contribution
completely prescribed
easy to replicate
kind of studied phenomena
is limited
Experiments - Compared
Experimental Method
• Manipulates IV and observes
effect on DV
• Comparable Conditions across
all levels of IV
• application limited
• cause-effect relationship
Correlational Method
• Observes IV and DV
• Further (extraneous) variables
may covary with levels of DV
• widely applicable
• ambiguous cause-effect
interpretations
Between-Subjects Design
• Experiments compare at least two conditions A and B
→ at least 2 levels of independent variable (IV)
• Subjects who participate might be placed into
condition A, B or both
→ 2 different types of experimental designs
• If subjects receive either level A or B but not both
→ between-subjects design
• If each subject receives both levels of IV (A, B), i.e.,
both levels exist within the same subject
→ within-subjects design (repeated measures design)
Between-Subjects Design
• Sometimes a between-subjects design must
be used. If the independent variable is
• a subject-variable (e.g., anxiety, gender,..)
• manipulated in a certain way that precludes
within-subjects measures (e.g., social Ψ
experiments), i.e., participating in one
condition makes it impossible for the same
person to be in a second condition
Between-Subjects Design
• Example (Sigall & Ostrove, 1975):
on the influence of physical attractiveness of
a defendant on recommended sentence
• written descriptions of a crime - asked to
recommend a jail
• IV1 = Type of crime (2 levels: burglary in
which woman stole 2,200 $ vs. swindle in which
woman induced man to invest 2,200 $)
• IV2 = Attractiveness of woman (2 levels: very
attractive vs. unattractive (vs. no photo)
Between-Subjects Design
Result
Attractiveness of woman
Crime
attractive unattractive
control
burglary
5.2 yrs
5.1 yrs
swindle
4.4 yrs
4.4 yrs
Between-Subjects Design
Result
Attractiveness of woman
Crime
attractive unattractive
control
burglary
2.8 yrs
5.2 yrs
5.1 yrs
swindle
5.5 yrs
4.4 yrs
4.4 yrs
Between-Subjects Design
Advantage
• subjects enter the study fresh and
naive with respect to procedures
Disadvantage
• large number of individuals needed
• differences between conditions might be due
to differences between groups
Between-Subjects Design
• with a small number of participants it could happen
that random assignment places all A-subjects into
one group → non-equivalent groups
Group 1 Short
Group 2 Long
1 N1
17
6 N6
25
2 N2
16
7 A1
14
3 N3
19
8 A2
16
4 N4
20
9 A3
17
5 N5
18
10 A4
15
__________________________________________
Mean
18.0
17.4
SD
1.58
4.39
Between-Subjects Design
• Creating Equivalent Groups
• Random Assignment
method for placing randomly selected
subjects into the different groups
• → equal probability for each subject to be
assigned to a specific condition
• → spread possible individual difference
factors evenly across conditions
Between-Subjects Design
Equal probability of assignment PLUS
Allow for relevant individual differences
Group 1
Short
Group 2
Long
1N
17
6N
27
2N
16
7N
26
3N
19
8N
26
4 A1
10
9 A3
17
5 A2
11
10 A4
15
__________________________________________
Mean
14.6
22.2
SD
3.91
5.72
_________________________________________
Between-Subjects Design
• Matching
Pair subjects together for a specific characteristic
and then assign randomly to groups. You need to
measure the matching variable in a reasonable manner.
• Example: obtain scores for test anxiety and then sort
subjects into pairs and assign subjects from each pair
randomly to the two groups (flip a coin)
P1
P4
N1 - N4
A2 - A4
P2
P5
N6 - N5
A5 - A1
G1={N1,N5,N2,A2,A1,A6}
P3
P6
N3 - N2
A3 - A6
G2={N4,N6,N3,A4,A5,A3}
→ Matched Pair Design (e.g. identical monozygotic twins)
Between-Subjects Design
Control
Group
IV
Level 1
DV
Experimental
Group
IV
Level 2
DV
Sample
1. Random Sample
2. Matched
Identical conditions except
manipulation of IV
Comparison
Equivalent Groups
Between-Subjects Design
•
Manipulated vs. Subject Variables
• Comparisons may be made also between groups of
people who differ from each other in ways not
manipulated by experimenter
• → comparison between factors which are nonmanipulated variables or ex-post-facto variables
→ subject variables
• Refer to already existing characteristics of the
participants in the study (e.g., gender, intelligence,
age, RT)
Example
Group study of relationship between anger level and
cardiovascular responsiveness (CR) to film scenes
a) induce different levels of anger and measure CR
b) select two groups differing in pretest-level of anger
• here subjects cannot be randomly assigned to groups
• Pre-test: measure of participants before an
experiment in order to balance or compare groups, or
to assess change by comparison with scores after the
experiment
• → No "true" experiment !
Between-Subjects Design
•
Problems with subject variables
experimenter can not hold all other variables constant
extraneous variables can not be controlled
• e.g., person with higher scores in anger may also
differ in the way they cope with everyday life
situations; they might be prone to have
cardiovascular problems, ...
• → no cause-effect conclusions can be drawn in
contrast to a confound free experiment
Studies using subject variables are also called ex post
facto studies or quasi-experiment
Between-Subjects Design
•
Ex post facto research
study where pre-existing and non-manipulated
variables among people are measured
• Quasi-experiment
study in which experimenter does not have control
over the allocation of participants to conditions
and/or the independent variable
• Group difference study
study, which compares the measurement of an existing
variable in two contrasting groups (male vs. female,
intro- vs. extrovert)
University A
Control Group
Traditional
Teaching Method
DV
University B
Experimental Group
New Interactional
Teaching Method
DV
Nonequivalent Groups
Comparison
Quasi-experiment
Quasi-experiment
Control
Group
No
Treatment
DV
Experimental
Group
Treatment
DV
Dyslexics
Voluntary participation in
dyslexia treatment program
(i.e., self-selection)
Comparison after 3 years
Nonequivalent Groups
Summary
• True Experiment
– Manipulation of IV
– Control of confounding variables
• Quasi-Experiment
– Manipulation of IV
– No control of confounding variables