PSY 250
Exam 3 Review
RESEARCH STRATEGIES
 Experimental strategies are not determined solely by potential
weaknesses – EVERY study has some weakness.
 Rather, the difference between true and non or quasi experiments
is determined by the amount of control over assignment to groups
(between subjects) or order of conditions (within subjects)
RESEARCH STRATEGIES
 Correlational designs are NOT between subject designs with
discrete categories or groups you are comparing!
• This is probably ex post facto or differential groups design
 Not every design that compares two variables is correlational!
BETWEEN VS. WITHIN
 Between
•
DIFFERENT individuals give data point at each level of the IV.
Therefore, you are comparing the average scores of one group of
people to the average scores of (a) DIFFERENT group(s) of people
 Within
• The SAME individuals participate and give a data point at each
condition of the experiment (or each level of the IV).
• Thus, you are comparing an individual’s score under one condition to
their own scores in a different condition(s)
VARIABLES
 If you are looking at the effects of more than one variable on another
variable (DV), then you have multiple IVs (i.e.. a factorial design)
 If one IV is between and another is within, you have a mixed factorial
design
 You are then probably looking at main effects of IVs PLUS their
interactions
• i.e. does the DV at one level of one IV depend on the level of another IV
• E.g. do girls perform better with fewer classmates in a classroom while
boys perform better with more classmates in a classroom? (interaction
with number of classmates (IV 1) and gender (IV 2)
INTERACTIONS CONT.
 If both males and females do better (and about the same amount
better) with fewer classmates then gender and number of classmates
do not interact
 However, if the improvement is much greater for one gender than
the other, there may be an interaction
MAIN EFFECTS
 If males generally perform better than females (or vice versa), but class
size does not effect performance, there is a main effect of gender but not
class size and no interaction
 If both genders do equally well, but both do better in smaller classes,
then there is a main effect of class size, but not gender
 If males do better than females but both do better in smaller classes,
there are main effects of both gender and class size but no interaction
 There can be main effects and no interaction AND interactions without
main effects
100
100
80
80
60
60
40
40
20
20
0
0
dressy
dressy casual sloppy
Males
Males
Females
Females
80
males
females
60
40
sloppy
casual
dressy
casual
sloppy
Small
large
males
80
78
females
70
69
Small
large
males
85
72
females
80
68
Small
large
males
84
81
females
83
71
SEEING INTERACTIONS
•
Is there an interaction?
•
What numbers do we
compare to see if there is a
main effect of:
•
•
•
Gender?
Class size?
Are there main effects?
Small
large
males
80
78
females
70
males
• What numbers would we
Small
large
85
72
females
68
Small
males
84
females
83
SEEING INTERACTIONS
large
71
place in the missing cell to
create
•
•
An interaction?
No interaction?
1 . D I F F E R E N T I A L R E S E A RC H
DESIGN (NE)
 Also called ex post facto research
 Compares pre-existing groups defined by participant variable
 E.g. shyness scores from single child vs. child with siblings
 Existence and description of relationships
 Similar to correlational design but different data and analysis
2 . P O S T T E S T- O N LY N O N - E Q U I VA L E N T
CONTROL GROUP DESIGN (NE)
 Also called static group comparison
 Applied settings
 Measure effectiveness of treatment with pre-existing participants
 Similar but nonequivalent participants used as control condition
X
O
O
Exp. Grp
Control
3.
P R E T E S T – P O S T T E S T N O N - E Q U I VA L E N T
CONTROL GROUP DESIGN (QE)
 Stronger version of posttest only design
 Both control (C) and experimental (E) groups measured prior
to treatment and again after E group receives treatment
 Shows if groups are similar on the DV before manipulation of
IV
 Also controls for time related changes in DV indep. of IV
 Reduces threat of both assignment bias and time related threats
Grp.
O
O
X
O
Exp.
O
Control
1 . O N E - G RO U P P R E T E S T –
POSTTEST DESIGN (NE)
 One pre and one post-test measurement
 E.g. voter’s confidence in electoral candidate before and after
televised debate
O
X
O
2. TIME SERIES DESIGN
(QE)
 Treatment is manipulated by researcher
 Series of observations for each participant before and after
treatment or event
 E.g. Measures of stress weekly for 2 months preceding and
following introduction of aromatherapy in workplace
O
O
O
X
O
O
O
3. I N T E R RU P T E D T I M E S E R I E S
DESIGN (QE)
 Treatment is NOT manipulated by researcher
 E.g. Depression measured monthly for 3 months before
and after Christmas
 Works with predictable event like decriminalizing marijuana
 For unpredictable events like Katrina, rely on archival data
 Can see trends in data before treatment
 Can observe long-term changes following treatment
 But other changes can coincide with treatment
• E.g. cold weather/snowfall and Christmas
4. E QU I VA L E N T T I M E –
SAMPLES DESIGN (QE)
 Treatment is repeatedly administered and removed during series of
observations
 E.g. introducing music in the workplace – turning it on and off and
measuring worker concentration at regular intervals weekly
O
O
O
X
O
N
O
 Best used when treatment effect is expected to be temporary
 Hard to determine causality if treatment effect is permanent
X O
CORRELATIONAL STUDIES
 Simply measures 2 variables [usually two scores (X and Y) from same individual] or
scores on 1 variable between 2 related individuals
 Criterion (Y) and Predictor (X) variables
 Degree and nature of relationship
• descriptive or predictive
 Correlation coefficients
+1.00 to -1.00
 No attempt to explain relationship
 No attempt to manipulate or control variables