l 5 Flashcards
Factorial design
more than one IV
– Each IV is called a factor
Notation system in Factorial design
– Digits represent IVs
– Values represent the # of levels
• e.g. 2x3 factorial ( “two by three”)
– 2 IVs, one with 2 levels, one with 3 = 6 conditions
• e.g. 2x4x4 factorial
– 3 IVs, with 2, 4, and 4 levels = 32 conditions
Main effects
the separate effects of each
independent variable on the measure
e.g. main effect of training type
Research example
Gladue & Delaney (1990)
Gender differences in perception of attractiveness of men and women in bars
• Possible alcohol consumption confound?
– Found no relationship between alcohol consumption
and attractiveness ratings
• Possible confound of actual attractiveness
differences at different times of night?
– Replicated their result using standard photographs
– Note: chose photos of moderate attractiveness to
avoid floor or ceiling effects
interaction effect
When the effect of one independent variable depends on the level of another
• e.g. the effect of psychotherapy is larger when
the receiver is highly motivated to change
• e.g. using a cell phone affects driving
performance more at night than during the day
• Some effects may not be detectable without
using a factorial design
– e.g. a study of lecture vs lab emphasis alone would
find no effect, but only because there is an opposite
effect for science and humanities majors
• In the presence of an interaction, one must
interpret main effects with caution
Grant et al interaction example
“Context dependency for meaningful text material
was examined using two standard academic
testing techniques: short answer (recall) and
multiple choice (recognition). Forty participants
read an article in either silent or noisy conditions;
their reading comprehension was assessed with
both types of test under silent or noisy conditions”
person by environment design
we have both unmanipulated variables (ie. person) and manipulated variables (ie. environment)
mixed design
we have both betweensubjects and within-subjects variables
Example mixed design
• Cohen et al. (2004). Fatal Attraction: The Effects of
Mortality Salience on Evaluations of Charismatic, TaskOriented, and Relationship-Oriented Leaders.
• A study was conducted to assess the effects of mortality
salience on evaluations of political candidates as a
function of leadership style … we hypothesized that
people would show increased preference for a
charismatic political candidate and decreased preference
for a relationship-oriented political candidate in response
to subtle reminders of death.
• “Following a mortality-salience or control induction, 190
participants read campaign statements by charismatic,
task-oriented, and relationship-oriented gubernatorial
candidates; evaluated their preferences for each
candidate; and voted for one of them.”
• 2x3 mixed factorial, with counterbalancing
• IV1: mortality induction or control (between-subjects)
• IV2: leadership style of political candidates: charismatic,
task-oriented, and relationship oriented (within-subjects)
• DV: evaluation of candidates
Example PxE Design
• Inzlicht & Ben-Zeev (2000). A threatening intellectual
environment: Why females are susceptible to experiencing
problem-solving deficits in the presence of males.
• Is a situational cue, such as gender composition,
sufficient for creating a threatening intellectual
environment for females—an environment that elicits
performance-impinging stereotypes?
• Male or female subjects completed a difficult math test in
3-person groups, each of which included 2 additional
people of the same sex (same-sex condition) or of the
opposite sex (minority condition)
Example Mixed PxE Design
• Strayer & Drews (2004). Profiles in driver distraction:
effects of cell phone conversations on younger and older
drivers.
• “Our research examined the effects of hands-free cell
phone conversations on simulated driving
• 2x2 PxE mixed factorial
• IV1: age of drivers (subject variable)
• IV2: driving with and without cell phones
(manipulated variable and a repeated measure)
• DV: reaction time
• Two main effects, no interaction
– Younger drivers outperformed older drivers
– Cell phone use impaired driving
Summary of designs
• Factorial designs allow us to evaluate the effects
of multiple IVs on the DV
• There are different types of factorial designs,
depending on how you manipulate your IVs.
– Between-subjects, repeated measures, mixed, PxE
• Main effects of each IV and interactions among
IVs are the key results from factorial designs.
APA Ethical Principles and Code of Conduct
• Guidelines for ethical behavior for the practice of
research, clinical work, and teaching in psychology
• “Designed to guide and inspire psychologists to the very
highest ideals of the profession”
• Code contains:
– 5 general principles
– 89 standards of practice
Ethical History
• Nuremberg Code (1947) – Nazi doctors put on trial • Declaration of Helsinki (1964) – Revision of the Nuremberg Code • Belmont Report (1979) – In part due to Tuskegee Syphilis Study – Ethical principles and applications that inform APA Ethical Guidelines
Five general principles in APA Ethical Principles and Code of Conduct
- Beneficence and Nonmaleficence
– Constantly weigh costs & benefits; protect from harm;
produce for greatest good - Fidelity and Responsibility
– Be professional; constantly be aware of responsibility to
society - Integrity
– Be scrupulously honest - Justice
– Always treat people fairly - Respect for Peoples’ Rights and Dignity
– Safeguard individual rights; protect rights of privacy and
confidentiality
