Research Design Flashcards
Types of Research Designs
Experimental
- true experiment
- quasi-experiment
or Non-Experimental
- correlational
- descriptive/observational
True Experiments
→ highest level of internal validity, can make the strongest causal claims with a true experiment, but we lose some external validity
Requirements for a True Experiment
- Systematic manipulation of 1 or more variable(s) between or within groups
- Guarantee temporal order of cause effect
- Observe covariation between variables
- Minimise alternative explanations/confounds - through random allocation
- Random assignment to each condition/group
- Minimise alternative explanations/confounds
Advantages of a True Experiment
- Isolation of a single variable
- Systematic manipulation of the variable (operationalising, choosing controls, etc means more control over determining if the variable is really the thing that might cause it)
- Doing so allows us to minimise numerous alternative explanations
- High levels of internal validity
Random Assignment
randomly assign participants to each of the groups to reduce the likelihood of systematic differences between the participants in the group which undermine internal validity
- Can be sure we have eliminated confounds
- controlling for bias in group allocation
- internal validity
Random Sampling
approach to recruiting subjects for your study
- Try to sample different elements of the population proportionally
- More representative
- Applies to all forms of research design
- External validity
- c
Two-way design
most common, two IV’s for example video games and also the duration of play
- Helps look at the difference between a wider range of combinations to determine what contributes to this
- Can examine the difference between the groups and any interaction
- Is there a difference between the amount of time played
- Is there a difference between the type of game
Within-subject design
can control third variables in other ways
- Use the same participants in different conditions rather than different groups
- Allows someone to eliminate individual differences
- Sometimes called a repeated measures design
- Systematic manipulation of IV still
Advantages and Limitations of within-subject design
Advantages
- Can be statistically powerful - remove error noise
- Easier to get a significant result
- Accounts for individual differencesLimitations
- Fatigue
- Practice
- Carry-over
between-subject design
→ comparing groups rather than conditions
LSD and Psychopath Psychotherapy
- Treatment of psychopaths in prison
- One reason it’s hard to treat psychopaths for violent crimes is that they lack empathy, LSD in high doses creates an “ego death”
- “First-ever marathon nude psychotherapy session for psychopaths. Raw, naked, LSD sessions for eleven days straight
- Theory that it would foster a sense of empathy
- Obviously didn’t work
Follow-up in the 80s
- Normal (recidivism) rate of offending is 60%
- Those with therapy is 80%
Characteristics of Quasi Experiment
- Research only has partial control over the independent variables
- Participants are assigned to groups or conditions without random assignment
Two types
- Person x treatment
- Natural experiments → less relevant for psych
- Useful when random assignment is not possible or ethical or when researchers don’t have control over what is being measured (race, ethnicity, age)
- use dependent and true independent variables but also use quasi-independent variables
Quasi Independent Variables
- not manipulated by the experimenter
- random assignment is not possible
- used in the same way as a true independent variable
- split people into groups based on the variable
Person/Attribute Variables
Individual difference variables
- Can vary along a spectrum
- Can be based on diagnostic criteria
- Use these variables most commonly for comparing groups – grouping variables
- We can use these to compare any differences on a dependent variable when random assignment is not possible
- Used because we can’t control in any other way
- Must be measured prior to the experiment, if not there are issues with internal validity, require temporal sequence to make sure the experimenter didn’t cause the difference
Extroversion vs Introversion Scale (Attribute Variable Example)
- Select random group of participants, complete a personality test which measures a range of personality traits
- Examine the scores and then select a group that score high in extroversion and introversion
- The attribute is measured and then participants are split into groups on the basis of their score
How do we split
- Splitting these attribute variables into high and low is a common practice, past q1 and q3 for example
- Not the best method statistically (quite crude)
Attribute of interest: usually normally distributed in the population
