Week 2: methods Flashcards
methods of measuring individual differences
- Survey / self-report measures
- Observational measures
- Performance measures
Self-report measure
Typically involve presenting a list of statements and asking participants the extent to which they agree/disagree with them
self-report advantages
Low cost and easy to administer in large scale (even online)
self-report disadvantages
– Respondents’ tendency to give socially desirable answers
– Respondents’ tendency to agree (acquiescence bias)
– Only measures thoughts, (explicit) attitudes, and self-perception
– Requires respondents’ self-awareness (introspection)
Experience sampling method
- Ask participants to report their thoughts, feelings, and/or behaviours repeatedly over a certain period of time (e.g., 2 or 3 weeks)
- Response frequency could be daily (diary studies) up to several times a day
- Alternatively, participants could be signalled by a mobile device to fill in a brief questionnaire at a random time
- Potential problem:
– The very act of self-monitoring can influence what is being measured
Observational measures
Typically involves recording what is being done or how often something is done through observation by a third person (from tally to videotaping)
observation advantages:
can be used when it is impossible or inappropriate to give instructions to a participant; can be used in naturalistic settings
observation limitations
– can only measure overt behaviours
– scoring may be influenced by observer biases
* Computerised scoring (as in eye tracking) can minimise observer biases
Performance measures
- Intelligence, reading/math performance, etc.
- Typically accuracy measures (in terms of error rates, percentage correct, percentiles, etc.)
- Response times (RT) as additional performance indicator
- Differences across individuals reflect differing abilities,
- Differences across tasks reflect differences in information processing mechanisms
performance measures advantages
objective (rather than self-report which relies on self-awareness)
performance measures limitations
their relationship with real-world behaviours (i.e., ecological validity) is not always clear
Can we measure the unconscious mind?
Cognitive tasks like implicit association test and priming are used to measure unconscious cognitive processing
Priming paradigm
participants are exposed to a certain stimulus (prime), and their response to a subsequent stimulus (target) is measured
* The prime is supposed to activate mental representations which could affect processing of the subsequent stimulus
* In masked priming, the prime is presented followed by a junk visual material (mask). This prevents the prime from entering conscious processing
Masked priming task - Moret-Tatay et al. (2020)
○ When the name matches the picture, participants are faster than without the masked prime.
Factor analysis
Factor analysis is a statistical technique used to reduce a large number of variables into fewer “factors”
The rationale is to analyse the patterns in which variables (items) vary together (covariance); variables (items) indicating the same underlying construct are expected to covary
Exploratory factor analysis (EFA)
does not assume a particular factor structure but uses the data to determine:
– The number of factors
– Correlations between a variable (item) and a factor, called factor loadings, are computed and examined
– The higher the factor loading (regardless of sign), the more important the variable is to the factor
in EFA the number of factors as well as criteria for including a variable in a factor is the researcher’s decision