RESEARCH AND GOALS OF MEASUREMENT Flashcards
REMINDERS > INTERNAL AND EXTERNAL VALIDITY
> To determine whether exclusive relationships exist between certain variables ( internal validity)
Does playing Sudoku improve working memory?
> To determine whether such relationships translate to individuals
and situations in the real world ( external validity)
Would playing Sudoku improve memory capacity in children and adults?
Causation
Determining causation is the ultimate research goal
•The first step in determining possible causation is to
choose a causal model
•A causal model (theoretically) should include
variables which are related in a sensible way
•That is, it is possible that one variable could be
causing (leading to changes) in another
CAUSAL MODELS
The most basic causal models only have two variables
Causal Variable > Consequence Variable
Independent Variable > Dependent Variable
Predictor Variable > Outcome Variable
Causal, Independent Predictor variables are thought to cause changes in another variable
Positive relationship: An increase in the values of the causal produces an increase in the values of the consequence variable
Negative relationship: An increase in the values of the causal variable produces a decrease in the values of the consequence variable
Independent Variables: Levels
Can have multiple levels when a variable is used
Can be male/female ( 2IV)
Can be playing or not playing sudoku (2IV)
Can be, playing for 1 hours, 2 or 3 ( 3IV)
COVARIATES
Variable that may also affect the dependent (usually a weaker association)
E.g., Education (in addition to Sudoku) may improve working
memory
Typically not of primary interest to the researcher
Should be taken into account (measured or controlled) when designing the research
CONFOUND
> If the covariate is a more sensible explanation then it is a confound
That is, the effect we are supposedly interested in is being confused for the effect of another variable
Gender/Sex as a Causal Variable
•Gender is a poor choice of causal variable
•While it might be convenient, it represents too many possible confounds
•We are often interested in gender/sex differences, but the explanation for those differences
is complex
•Being male or female is accompanied by complex number of factors
Socialisation
Recreational activities
Hormones (gender vs. sex)
Cultural norms
Occupations
Proximity
•Ideally, you want to specify models which include two very proximate variables
i. e., they are not separated by other potential variables
i. e., the causal variable is very closely associated
Causation vs. Association
•In research settings we are not always able to demonstrate or support a causal relationship
This is often because of practical and ethical constraints
Sometimes, we can only measure variables
E.g., rather than manipulate them
This leaves us only able to determine if they are associated but not if one likely causes the other
So we have to be careful about how we talk about causation
LECTURE ATTENDANCE»_space;> ACADEMIC PERFORMANCE
> Not good causal model > other variables which might affect performance
DEPRESSION»_space; ANXIETY
> strong evidence there is a + association
> however more variables involved
PARENTAL STATUS»_space;> EXAM PERFORMANCE
>Not good model
>Other confounding variables could exist
Models are never “proven”
•In science, we typically do not use the word “prove” when talking about models •Instead, we use terms like: “support" “find evidence for" “positively link
•Just because the data supports a model, it doesn’t mean that model is proven as it could just be a random finding
Advanced Causal Models
General Aggression Model
(Anderson & Bushman, 2002)
The General Aggression Model (GAM) is a comprehensive, integrative, framework for understanding aggression. It considers the role of social, cognitive, personality, developmental, and biological factors on aggression.
Uses multiple dependent and independent variables
Causation needs Explanation
- Psychology is about explaining phenomena
- Not just describing it
- Look for explanations not just descriptions
Description: Women who read more fashion magazines have more eating disorder symptoms
Explanation: Frequent exposure to images of women who possess idealistic physical characteristics communicates a normalized body image which does not represent most women.
Women who adopt this normalised image may then engage in compensatory behaviours, such as
restricted eating and purging, in an attempt to narrow the perceived discrepancy between their
own physical appearance and that of an ideal body image.
- An explanation can be the difference between psychologicaland non psychological research
- When reading papers, look for explanations
It can be the difference between a good paper and a weak paper
Sometimes the quality of the journal can help
Another helpful tip is to look at the title of the journal or the aims and scope
CAUSAL MECHANISM
•When you write an introduction for an
assignment, you should include an explanation
> It must clear why how one variable is thought to
affect the other
> E.g. what are the underlying processes or pathways
that lead to the outcome you are expecting?
•This explanation is referred to as the causal
mechanism
Sometimes there are multiple causal mechanisms
Focus on the simplest or easiest to explain
You want to be succinct and clear
You will need to cite other research to support any causal mechanisms you propose in your assignments
There is almost always some evidence available to help you explain the association between two variables
DATA
Data can be classified in a number of ways:
1.By the TYPE of instrument used to collect it
>Different instruments will yield different data depending on the scales (units) they employ (i.e., volume vs.
2.The SIZE of the set of data collected
E.g., single case, multiple case & metadata
3. STAGE of the process
Raw or transformed
Standardised
Summed
Averaged
Percentages
Frequencies
DATA INSTRUMENTS
•Questionnaires
SURVEY
>mixture of questions
>Often unrelated (gender, age, ethnicity)
INVENTORY
>questions capturing a similar concept
>usually published
>good measurement properties
•Tests APTITUDE (e.g., WAIS, WISC) problem solving perceptual reasoning working memory ACADEMIC/SKILLS PERFORMANCE >assessment of prior learning >general knowledge
DATA SOURCES
•Archives
e.g., education, criminal, and medical records
•Experimental tasks
a.Published measures
Iowa Gambling Task ( Bechara et al., 1994)
Wisconsin Card Sorting Task (Milner, 1963)
Implicit Association Task (Greenwald et al., 1998)
b.Novel measures
Can vary depending on researcher requirements
c.•Physiologocal Measures
Physical indicators of internal/external states
heart rate/blood flow
skin conductance
salivation
EEG, MRI, fMRI
body temperature
perspiration
