Transcript Psychology 242, Introduction to research

Psychology 242
Introduction
to Research
1
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Psychology 242, Dr. McKirnan
Multiple independent variables
4/14/09
 Testing hypotheses about > 1 independent variable
 Factorial Designs: Main effects, Additive Effects,
Interactions
Examples of complex experiments
 The interaction of drug use & attitudes on sex risk
among gay men
 3 Independent variables: alcohol and behavioral
disinhibition
 The interaction of “nature” and “nurture”: Genetics &
stress and depression
4/16/09
Psychology 242, Dr. McKirnan
Multiple independent variables
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Multiple independent variables
 Testing hypotheses about

> 1 independent variable
 Factorial Designs: Main effects, Additive
Effects, Interactions
Examples of complex experiments
 The interaction of drug use & attitudes
on sex risk among gay men
 3 Independent variables: alcohol and
behavioral disinhibition
 The interaction of “nature” and
“nurture”: Genetics & stress and
depression
Psychology 242, Dr. McKirnan
Multiple independent variables
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Main effects
Your paper tested a single Main effect:

Single Independent Variable [IV]



Experimental group v. control group
Placebo v. Dose 1 v. Dose 2, …etc.
Experimental groups
[true experiments]
Simple group contrast


Male v. female
School 1 v. school 2, …etc.
Naturally occurring groups
[quasi-experiments]
This tests a relatively simple theory:
 Links one hypothetical construct to one outcome

Arousal  performance

Gender  sex-role attitudes
 Assumes the main effect is independent of other key
variables
Psychology 242, Dr. McKirnan
Multiple independent variables
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
4
Example of main effect test; real data
Do stressful life events lead to more
depression?

Men were sorted into 5
groups, corresponding to #
major life stressors they
experienced from age 21 to
26.

At age 26 men in groups 3 &
4 were significantly more
likely to have lifetime major
depression episode than
groups 0  2
Number of major stressful events
(Ages 21 to 26)
Partial data from Avshalom C., (2003), Science Magazine.
Psychology 242, Dr. McKirnan
Multiple independent variables
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Multiple variables in psychological research
Multiple Independent variables allow us to
test more complex theories / hypotheses:

Link > 1 hypothetical construct to an outcome.
 Arousal and gender  performance
 Drugs and expectations  sexual risk

Test if an effect depends upon other key variable(s).
 Variable 1 affects the outcome
only at one level of variable 2
 Variable 1 has a different effect
on the outcome at different
levels of variable 2.
Psychology 242, Dr. McKirnan
Multiple independent variables
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Designs with > 1 independent variable
A. Including a ‘control’ variable as an I.V.
 e.g., gender, age, race, etc.
 test if the I.V. has the same effect within both
groups
B. Testing hypotheses re: 2 or more I.V.s
1. test separate, ‘main effects’ of each I.V.
(Do each of these variables significantly affect the outcome?)
2. test ‘additive’ effects of > 1 I.V.s simultaneously
(What is the combined effect of these variables?)
3. test interaction of 2 or more I.V.s
(Does the effect of one I.V. on the outcome depend upon a
second variable...?)
Psychology 242, Dr. McKirnan
Multiple independent variables
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Multiple independent variables
 Testing hypotheses about > 1
independent variable
 Factorial Designs: Main

effects, Additive Effects,
Interactions
Examples of complex experiments
 The interaction of drug use & attitudes
on sex risk among gay men
 3 Independent variables: alcohol and
behavioral disinhibition
 The interaction of “nature” and
“nurture”: Genetics & stress and
depression
Psychology 242, Dr. McKirnan
Multiple independent variables
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Example: factorial design testing 2 IVs
8
Hypothesis: Coping skills delivered by a peer help
diabetics maintain blood sugar.
Independent
Variables:
Skills training
Trainer
Values:
None
(Placebo / control grp)
High
(experimental group)
Nurse (“Standard of care”)
Peer
Psychology 242, Dr. McKirnan
Multiple independent variables
(experimental group)
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Example of a factorial design for testing 2 IVs:

The hypothesis rests on the interaction of two
variables

More complex theory of skills training.
Independent Variable 1
Experimental v. control groups
Psychology 242, Dr. McKirnan
4-group
factorial Design
Skills training
Distraction
Peer trainer
DV = M glucose control
DV = M glucose control
Nurse
DV = M glucose control
DV = M glucose control
Multiple independent variables
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Basic factorial design
Each “cell” of
the design
represents both
IVs:
Independent variable 1
Data Table No skills
(Distraction)
M
peer, no
skills
Nurse trainer M
Nurse,
no skills
Peer trainer
Independent
variable 2
Skills
Training
M
M
peer,
skills
Nurse,
skills
Data for each combination of conditions
Psychology 242, Dr. McKirnan
Multiple independent variables
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Basic factorial design data table: 2 I.V.s
This is a 2 x 2
factorial design:
 4 data cells
 each with a M
value for the D.V.
Independent variable 1
Data Table No skills
(Distraction)
Peer trainer
Independent
variable 2
Row Ms
M peer, no M peer, skills M
skills
Nurse trainer M nurse, no
skills
Column Ms
Skills
Training
M no
skills
Peer
trainer
M Nurse
trainer
M nurse,
skills
M skills
The “Marginals” show overall Ms for each I.V.:
 Skills v. no skills (a.k.a. main effect for skills…)
 Peer v. nurse trainers (trainer main effect…)
Contrasts among individual cells show any interaction
effects.
Psychology 242, Dr. McKirnan
Multiple independent variables
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Testing Main Effects (hypothetical data)
Example of
(made up) data
showing a main
effect
Data set 1. No skills
(Distraction)
Skills
Row Ms
Training
Peer
14
60
37
Nurse
12
58
35
Column Ms
13
59
36
 Glucose control
is enhanced by
skills training
 Change is the
same for both
training groups.
60
50
40
30
20
10
0
Distraction
Peer Trainer
Psychology 242, Dr. McKirnan
Multiple independent variables
Skills Training
Nurse Trainer
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Alternate display (hypothetical data)
An alternate display of the same main effect data
60
Skills training helps,
by about the same
amount no matter
who it is delivered
by…
50
40
30
20
10
0
Distraction
Skills Training
Peer Trainer
Psychology 242, Dr. McKirnan
Nurse Trainer
Multiple independent variables
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Two (additive) Main Effects
Psychology 242
Introduction
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Data set 2.
These marginals
show a main
effect of trainer
No skills
(Distraction)
(Peers do better
than nurses).
40
80
60
Nurse
12
40
26
Column Ms
26
60
43
50
60
40
50
30
Row Ms
Peer
And of skills
training:
60
Skills
training
Getting skills
training helps
about the same
in both groups
40
20
30
10
20
0
10
Peer
Nurse
(hypothetical data)
Psychology 242, Dr. McKirnan
0
Distraction
High skills
Multiple independent variables
…but contact
with a peer is
generally more
helpful
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Additive Main Effects (hypothetical data)
Putting these effects together shows a very
high value for patients who get skills training
by a peer…

80
70
60
50
40
30
20
10
0
Distraction Condition
Peer Trainer
Psychology 242, Dr. McKirnan
Enhanced skills
Nurse Trainer
Multiple independent variables
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Additive main effects: alternate display
Alternate display of additive effect of two
variables
General effect of
trainer: peers do
better than nurses
no matter what the
intervention…
80
70
60
50
40
30
20
10
0
Distraction
Enhanced skills
Peer Trainer
Psychology 242, Dr. McKirnan
…AND, getting
skills helps,
whether they are
delivered by a
nurse or a peer…
Nurse Trainer
Multiple independent variables
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Additive main effects: alternate display, 2
Alternate display of additive effect of two
variables
These two effects
“add up”:
Skills delivered by
a Peer have the
best results.
80
70
60
50
40
30
20
10
0
Distraction
Enhanced skills
Peer Trainer
Psychology 242, Dr. McKirnan
Nurse Trainer
Multiple independent variables
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Introduction
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Example of a
(made up)
interaction of
trainer by skills
condition
 Skills training
made a difference
 But
18
Interaction Effects (hypothetical data)
only among
patients trained by
a peer.
No skills Skills
Data set 3.
(Distraction)
Row Ms
training
Peer trainer
12
80
46
Nurse trainer
12
20
16
Column Ms
12
50
31
80
70
60
50
40
30
20
10
 For patients trained
by a Nurse, training
had little effect
Psychology 242, Dr. McKirnan
0
Distraction
Peer trainer
Multiple independent variables
Enhanced skills
Nurse trainer
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Alternate Display (hypothetical data)
Alternate display: interaction between
two variables
Large effect of training
90
80
70
60
50
40
30
20
10
versus distraction,
…but only for the peer
trainer not the nurse
Overall M for
skills training
Distraction
Overall M for
distraction
(placebo)
Skills
training
0
Nurse trainer
Peer trainer
Interaction: the effect of the 1st Independent Variable
(training) depends upon the 2nd IV; peer v. nurse.
Psychology 242, Dr. McKirnan
Multiple independent variables
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Multiple independent variables
 Testing hypotheses about > 1
independent variable
 Factorial Designs: Main effects, Additive
Effects, Interactions
Examples of complex experiments
 The interaction of drug

use & attitudes on sex
risk among gay men
 3 Independent variables: alcohol and
behavioral disinhibition
 The interaction of “nature” and
“nurture”: Genetics & stress and
depression
Psychology 242, Dr. McKirnan
Multiple independent variables
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Example of interaction effect; AIM study
Sexual Risk among gay & bisexual men who
combine alcohol and drugs with sex.
 People who use drugs during sex are more
likely to have unsafe (as well as more) sex.
 What causes that…
The drugs themselves (“disinhibition”)
Some characteristics of people who use them?
 Project: Awareness Intervention for Men study
of interventions for unsafe sex among MSM
who use drugs.
Psychology 242, Dr. McKirnan
Multiple independent variables
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Example of interaction effect; AIM study, 2
Sexual Risk…
McKirnan, D.J, Vanable, P., Ostrow, D., & Hope, B. (2001). Expectancies of sexual
“escape” and sexual risk among drug and alcohol-Involved gay and bisexual
men. Journal of Substance Abuse, 13, 137-154. Paper here.
Two “main effect” hypotheses:
 Drug use: More drug use & problems  more
sexual risk.
Attitudes: Using drugs to “escape” from having to
think about risk  more drugs + risky sex.
Interaction hypothesis:
 Drugs make people more risky, but primarily if they
also have “high risk” (“escape”) attitudes.
Implications for theory:
Interventions should focus on attitudes & expectations
as well as simple drug use.
Psychology 242, Dr. McKirnan
Multiple independent variables
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Example of interaction effect; AIM study, 3
Sexual Risk… Main effects:
Ignoring drug use, higher
escape motive  more risk.
Ignoring motives, higher
drug use  more risk.
30
30
25
25
20
20
15
15
10
10
5
5
0
0
Low escape motive
Psychology 242, Dr. McKirnan
High escape motive
Multiple independent variables
Infrequent / Alcohol
Frequent / Drugs
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Interaction of expectations x drug pattern
Sexual Risk… Overall / Interaction finding:
Drug users with strong
escape attitudes were
very risky.
Drug users without
escape attitudes were
less risky.

For men who did not use
drugs, attitudes did not
affect risk.
 

Drugs & attitudes
interact:
Drugs lead to risk primarily
in the “escape” group.
Psychology 242, Dr. McKirnan
Multiple independent variables
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Alternate display of interaction effect
Drug users:
risk is high, but
only for those
with strong
expectancies
No drug use:
risk stays low for
all participants
Psychology 242, Dr. McKirnan
Multiple independent variables
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Multiple independent variables
 Testing hypotheses about > 1
independent variable
 Factorial Designs: Main effects, Additive
Effects, Interactions
Examples of complex experiments
 The interaction of drug use &
attitudes on sex risk among gay men
 3 Independent

variables: alcohol and
behavioral disinhibition
 The interaction of “nature” and
“nurture”: Genetics & stress and
depression
Psychology 242, Dr. McKirnan
Multiple independent variables
Fillmore, M. T., & Weafer, J. (2004). Alcohol
impairment of behavior in men and women.
Addiction, 99 (10), 1237-1246. Article here.
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Example: 3 independent variables
Core Hypotheses:
1. Men are less able to inhibit behavior in response to alcohol
than are women.
2. Men get more aroused by alcohol, women get less aroused
Theories:
Social learning: Men are socialized to lessen behavioral control in
alcohol-related situations, women socialized to increase caution.
Bio-behavioral: Basic inhibitory mechanisms in men are more
reactive to alcohol and other drugs than in women
Operational Definition of “Behavioral Inhibition”:
 Participants are given a “go” prime + a “don’t press” stimulus
 Can they inhibit pressing the button?
Operational Definition of “Arousal”:
Two standard questionnaires: subjective stimulation & sedation.
Psychology 242, Dr. McKirnan
Multiple independent variables
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Experimental Design
Provide alcohol v. placebo beverages to men v. women.
(first 2 independent variables)
Provide 2 questionnaires:
 Subjective arousal / stimulation
 Subjective sedation
(First Dependent variable  represents a repeated measure)
Conduct a simple reaction time task … Participants told to:
a. press a button quickly in response to a “go”
stimulus,
b. do not press with a “no go” stimulus.
(Second Dependent variable)
Participants are first
a. primed to expect a “go” stimulus (“go” prime)
b. primed to expect a “no-go” stimulus.
(3rd Independent variable  also a repeated measure)
Psychology 242, Dr. McKirnan
Multiple independent variables
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Design:
1st
Dependent Variable
Participant
variables
Questionnaires
Alcohol:
Yes
No
Subjective
sense of
stimulation
Gender:
Male
Female
Subjective
sense of
sedation
First 2
Independent
Variables
First Dependent
Variable
1 measured, 1
manipulated
Psychology 242, Dr. McKirnan
29
Repeated measure:
each person gets both
questionnaires
Multiple independent variables
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Design:
2nd
Dependent Variable
Participant
variables
Participant
priming
Alcohol:
Yes
No
Expect
“go”
stimulus
Gender:
Male
Female
Expect
“no-go”
stimulus
First 2 I.V.s
Third I.V.
Repeated
measure: each
person gets both
conditions
Psychology 242, Dr. McKirnan
30
Multiple independent variables
Actual
target
stimulus
Button press?
“go”
no
“no-go”
yes
“go”
no
“no-go”
yes
Common
procedure
Assess “no-go”
condition only
Dependent
Variable:
Pressing in
the “no-go”
condition =
disinhibition
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Factorial design details
Full factorial design with a repeated measure:
IVs:
Gender
2 x 2 x 2 = 8 cells,
using 4 sets of
participants.
Alcohol Consumption
Priming condition
Male
Alcohol
“go” prime
½ the participants are
men, ½ women
“no-go” prime
(repeated measure)
½ get alcohol, ½
get placebo
No
alcohol
“go” prime
“no-go” prime
(repeated measure)
¼
¼ of participants
in each major cell
“go” prime
“no-go” prime
(repeated measure)
¼
Psychology 242, Dr. McKirnan
Female
“go” prime
“no-go” prime
(repeated measure)
Each participant gets
two conditions
Multiple independent variables
¼
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First Dependent Variable
Hypotheses:
1. Alcohol leads to significant mood changes v. a
placebo beverage
a. stimulation & arousal
b. Sedation
2. Mood changes vary according to participant
gender
1. Men  stimulation
2. Women  sedation
Statistical test: 3-way interaction…
Alcohol
v.
Placebo
Psychology 242, Dr. McKirnan
X
Male
v.
Female
Multiple independent variables
X
Stimulation
v.
Sedation
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1st
33
DV
Figure 3 Mean ratings of subjective stimulation and sedation on the BAES
under 0.65 g/kg alcohol and placebo in women and men.
Alcohol (v. placebo) made
men more stimulated.
Psychology 242, Dr. McKirnan
Alcohol made women
more sedated
Multiple independent variables
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Psychology 242
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Alternate portrayal of 3-way mood interaction
Placebo conditions do
not show much effect
The alcohol conditions
show a classic
“cross-over” effect
for gender & mood;
50
M BAES subscale scores
45
Men get aroused
40
35
Men, Alcohol
Men, Placebo
Women, Alcohol
Women, Placebo
30
25
20
15
10
Women get sedated
5
0
Stimulation
Psychology 242, Dr. McKirnan
Sedation
Multiple independent variables
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External validity: 3-way interaction
How much
external
validity does
this finding
have?
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Dependent variable 2: “disinhibition” of button press
Alcohol & gender results 1
Figure 1 Mean proportion of failures to inhibit responses to no-go targets following
go and no-go cues under 0.65 g/kg alcohol and placebo in women and men.
Alcohol “disinhbition” is much
stronger for men than for women
But only with a
“go” prime.
…not for the
“no-go” prime.
Psychology 242, Dr. McKirnan
Multiple independent variables
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Summary of the 3-way interaction
1. Alcohol (vs. no alcohol)
makes it difficult to inhibit
behavior
2. …primarily among men (v.
women)
3. …when they are
primed to act, (vs.
when they are
primed to keep from
acting).
How much
external
validity does
this finding
have?
Psychology 242, Dr. McKirnan
Multiple independent variables
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Multiple independent variables
 Testing hypotheses about > 1
independent variable
 Factorial Designs: Main effects, Additive
Effects, Interactions
Examples of complex experiments
 The interaction of drug use &
attitudes on sex risk among gay men
 3 Independent variables: alcohol and
behavioral disinhibition
 The interaction of

“nature” and “nurture”:
Genetics & stress and
depression
Psychology 242, Dr. McKirnan
Multiple independent variables
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Interaction example, 1
Interaction of genetics & stress on depression.
Overall hypothesis: stress “switches on” genes that
confer vulnerability to depression
Independent variables:


Variations in a gene that controls serotonin production
in the brain [a measured variable].
The number of “serious” stressful life events between
ages 21 and 26 [also a measured variable]
Outcome variables:




Symptom counts
Major depression episode
Suicide attempt
Others’ reports of depression
Psychology 242, Dr. McKirnan
Multiple independent variables
Avshalom C., et al. (2003).
Influence of Life Stress on
Depression: Moderation by a
Polymorphism in the 5-HTT Gene.
SCIENCE, 301 (July 18), 386-389
[www.sciencemag.org].
[See readings: summary, actual article.]
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Interaction example, 2
40
[See readings: summary, actual article.]
5 levels of stress.
4 outcome measures (DVs).
3 levels of genetic disposition.
Psychology 242, Dr. McKirnan
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Interaction example, 3
41
[See readings: summary, actual article.]
More stress = more depression on all measures
Psychology 242, Dr. McKirnan
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Interaction example, 4
42
[See readings: summary, actual article.]
But primarily among genetically vulnerable people
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Stress leads to depression only for those who
are genetically vulnerable.
This is illustrated by different stress 
depression effects for two key genotypes.
High vulnerability
Psychology 242, Dr. McKirnan
Multiple independent variables
Low vulnerability
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Interaction example, 6
44
[See readings: summary, actual article.]
Interaction is very strong in an analysis of
childhood trauma and depression.
People with no genetic
vulnerability:
childhood trauma has
no effect on
depression
People with increasing
genetic vulnerability:
More trauma  greater
likelihood of
depression.
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Multiple IVs; summary 1
Multiple Independent Variables / Predictors
tell us much more than simple main effects.
Main effect:

Test how one IV in
isolation affects the DV
# of major stressful events
(Ages 21 to 26)
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Multiple IVs; summary 1 Multiple Independent Variables / Predictors
46
tell us much more than simple main effects.
Main effect: One IV  one DV
Additive effects:

Two IVs each have a
main effect
80
70
60
50

One combination has
a particularly strong
effect on the DV
40
30
20
10
0
Distraction
Enhanced skills
Peer Trainer
Psychology 242, Dr. McKirnan
Multiple independent variables
Nurse Trainer
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Multiple IVs; summary 1 Multiple Independent Variables / Predictors
47
tell us much more than simple main effects.
Additive effects: Some variables may
combine with others to produce very
strong effects
Interaction effects:

One IV has a different effect
on the DV depending upon
another IV:
Emotional arousal
Main effect: One IV  one DV
The effect of alcohol on emotional arousal
depends upon gender.
IV 1: Emotional arousal
IV 2: Gender
Interaction:  Stimulation goes up if you are male.
 Sedation goes up if you are female.
Psychology 242, Dr. McKirnan
Multiple independent variables
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Psychology 242
Introduction
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Multiple IVs; summary 1 Multiple Independent Variables / Predictors
48
tell us much more than simple main effects.
Main effect: One IV  one DV
Increasing vulnerability:
More trauma  greater
likelihood of depression.
Additive effects: Some variables may
combine with others to produce
very strong effects
Interaction effects:

One IV has a different effect on
the DV depending upon another
IV:

One IV has an effect only
at one level of a 2nd IV:
No genetic vulnerability:
childhood trauma has no
effect on depression
The effect of childhood abuse on risk for depression depends
upon a genetic disposition.
IV 1: Level of trauma
Psychology 242, Dr. McKirnan
IV 2: 3 forms of 5-HTT genotype
Multiple independent variables
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Introduction
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Multiple IVs; summary 2
Multiple Independent Variables / Predictors:

Are critical to theory development and testing:
Changing sexual risk reduction requires that we understand both
peoples’ psychological dispositions and their drug use patterns.
Stress or other environmental events can “switch on” genes that create
psychological or other problems; genetic dispositions and environment
are not separate processes.

Establish “boundary conditions” to a theory:
when and among whom does a basic
psychological process operate?
Alcohol makes it more difficult to inhibit behavior, but primarily among
men.
Psychology 242, Dr. McKirnan
Multiple independent variables
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Introduction
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
50
Summary
Key terms:

Main effect

Additive effect

Interaction

Cross-over interaction

Factorial design

Repeated measure
Psychology 242, Dr. McKirnan
Multiple independent variables
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