Summary Exam 4 Research Methods & Statistics UvA Year 1
Introduction to Statistics - Lecture Notes
Statistical Methods for the Social Sciences, chapters 1-6 and 9-11, by Agresti & Finlay
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Universiteit van Amsterdam (UvA)
Psychologie
Research Methods & Statistics (7201704PXY)
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W1.1
Ch4 ETHICAL GUIDELINES
Morling Ethics in research:
- Treating participants respectfully Balance between the risk
- Not harming participants to participants and the
- Not targeting an already disadvantages social group value of knowledge
- Debriefing participants after the research has been conducted
The Belmont Report – Core ethical principles:
1. The principle of respect for persons
- Informed consent
2. The principle of beneficence: Taking precautions as a researcher to protect participants
from harm and to ensure their wellbeing
- Anonymous study
- Confidential study
3. The principle of justice: Ensuring that participants are representative of the kinds of
people that would also benefit from the study’s results
APA’s Five General Principles (for psychologists in general):
1. Beneficence
2. Fidelity and responsibility
3. Integrity
4. Justice
5. Respect for people’s rights and dignity
APA’s Ethical Standard For Research:
- Institutional review board (IRB): A committee responsible for interpreting ethical
principles and ensuring that research using human subjects is conducted ethically –
Consists of several people with different backgrounds
- Informed consent: The researcher’s obligation to explain the study to potential
participants in everyday language and to give participants a chance to decide whether
or not to participate
- Deception: Not allowed
- Through omission: Withholding information from participants
- Through commission: Actively lying to participants
- Debriefing → Especially important after deception
Research misconduct:
- Data fabrication: Inventing data to fit the hypothesis
- Data falsification: Influencing a study’s results
- Plagiarism: Representing the ideas or words of other’s as one’s own
Animal research:
- Caring for the animals as best as possible
- Making sure the research is valuable enough to justify the use of animal subjects
, - Guidelines:
1. Replacement: Finding alternatives to animal research
2. Refinement: Modifying experimental procedures to minimise animal distress
3. Reduction: Using as few animals as possible
Ch12
EXPERIMENTS WITH MORE THAN ONE INDEPENDENT VARIABLE
Morling Interaction effects: When the original independent variable depends on the level of another
independent variable
- Crossover interaction: Interaction between two independent variables that ‘depends’
- Spreading interaction: Interaction between two independent variables that occurs ‘only
when’…
Factorial design: A type of research methodology that allows for the investigation of the main
and interaction effects → Crosses two independent variables → Participant variables (=
variables that are not manipulated, such as age or gender) are also considered ‘independent
variables’ in factorial designs
- Factorial designs can test limits
- Factorial designs show moderators (= an independent
variable that changes the relationship between another
independent variable and a dependent variable)
- Factorial designs can test theories
↓
1. Main effects: The overall effect of one independent variable on the dependent variable
Interaction effects
(= are
themore
amount of independent variables that have an effect on the dependent variable)
important than main effects
2. Interaction effects:
- If there is a significant difference in the means; there is an interaction effect
- If the lines in the graph are parallel, there is no interaction effect → The lines
do not have to cross to indicate an interaction effect; they simply have to be
nonparallel
- For bar graphs: Imagine drawing a line to connect the tops of the two levels of
the two independent variables – If the lines in the graph are parallel, there is no
interaction effect
FACTORIAL VARIATIONS
1. Independent-groups factorial designs: Both independent
variables are studied as independent groups (E.g.: in a 2
×2 factorial design, there are four different groups of
participants in the experiment)
2. Within-groups factorial designs: Both independent variables are manipulated as
within-groups (E.g.: in a 2×2 factorial design, there is only one group of participants,
but they participate in all four combinations of the design)
3. Mixed factorial designs: One independent variable is manipulated as independent-
groups, and the other is manipulated as within-groups
, INCREASING THE NUMBER OF LEVELS
How many conditions in total? → Multiply all conditions!
Three-way-design: When a third independent variable is added (E.g.: a 2×2×2 factorial
design)
- Results in three possible main effects
- Results in three possible two-way interactions
Three-way-interactions: A two-way interaction that depends on the level of the third
independent variable
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