Variable - Elements of a Claim
variable: something that varies/can take on different values(quantity = numbers /quality = colors/labels/words)/changes
NOT CONSTANT
examples:
ex. you are an extroverted person - not a variable
ex. a student used active recall for studying for studying and received an A for a class - NOT VARIABLE (CONSTANT)
scientific if: multiple study strategies related to grades
ex. the customers who had sweet tea reported a high level of satisfaction - not variable
scientific if: compared to different drinks
ex. after doing regular exercise, people’s stress decreased - ish?
compares stress before and after exercise, high to low, could be clearer
conceptual vs operational variables:
conceptual: an abstract label for a concept being studies
also called constructs in psychology
ex. extroversion, stress, study strategy
operational: how do i observe it?
how a variable is actually represented in a study through manipulation, observation, measurement, etc.
more tangible, and often quantifiable
examples:
ex. self report scores on a questionnaire
ex. heart rate variability
ex. being asked to create a story about the concepts learned from class (or not)
manipulation: researchers actively create or control what the participants do or experience
manufactured/induced/created by researcher
variable being manipulated is called the independent variable
a study that involves at least one manipulated variable is called an experimental or quasi-experimental study (allows for causation statements)
quasi = not completely random (no random assignment)
may not be feasible for total random assignment, but still involves variable manipulation
examples:
ex. intake of drug or placebo controlled by researcher
ex. doing a task with or without a specific time limit instructed by researcher
ex. reviewing profiles with different photos, phots selected and presented by researcher
limitation: ethics, bias, are the variables/results “natural” and represent every day life vs are they artificial and yielding artificial results
strengths: can establish causation
observation: researchers observe naturally occurring behavior or other types of evidence
an observed variable can be used in any type of study
ex. dependent variable in an experimental study
ex. a predictor or outcome variable in a non-experimental study (completely naturally occurring variables, no manipulation, no independent/dependent labels)
examples of predictor/outcome:
ex. time spent of physical activity every day - naturally occurring (predictor)
ex. level of activation of a specific brain area (outcome)
ex. messiness of space after a visit (indicator)
is evidence collected from observation objective?
subjectivity in relating evidence to conceptual variables
subjective measures: participants use opinion to report on variables related to themselves or others
a subject measurement can be used in any type of study, similar to observed variable
may be the only option when a variable is related to someone’s internal mental process
exmples:
ex. self report on satisfaction level on a scale
ex. others’ evaluation of a worker’s performance on a scale
ex. clinician assessment of someone’s mental health on a scale
causation vs correlation - types of claims
frequency claims: focused on 1 variable at a time
examples:
ex. frequency or percentage of people doing one thing
ex. mean and standard deviation of the data on a variable
correlation: the 2 or more variables are related
causation : one (or more) variable causes another variable (or multiple variables)
these 2 claims can be used to described hypotheses (specific predictions) of findings
examples:
ex. warm (vs cool) room temperature will harm cognitive performance
variables: room temp, cognitive performance - causation statement
ex. individualistic cultural value is associated with pro social behavior
variables: cultural value, pro social behavior - correlation statement ex
ex. a new medicine vs placebo will decrease the symptoms lf a neurological disorder
variables: meds, symptoms - causation statement
ex. level of patience is tied to number of traffic violations
variables: patience, traffic violations - correlation statement
correlation descriptors:
stating the claim: if the predictor variable is related/associated/correlated to the outcome variable
non directional: stating 2 variables are related
social media activity and stress stress are related: predictor = social media activity, outcome = stress
directional positive: as 1 variable increase another increase, vice versa
performance in college and income are positively related: predictor = performance in college, outcome = income
directional negative: as 1 variable increases another decreases
sleep quality and fatigue are negatively correlated: predictor = sleep quality, outcome = fatigue
evidence needed for correlation: scatter plots
requires observations/measurements of both variables on same group of individuals
statistical analysis
direction: positive/negative
magnitude/strength: between -1 and 1
(-)1 = strongest
0 = no correlation
test of statistical significance
causation = evidence needed:
covariation:
need evidence on both IV and DV from same people
need to use statistical methods to examine the relationship
temporal precedence:
need evidence to support ordering of events: change in IV → change in DV
active control of IV by research (experimental design)
following the same people over time (longitudinal design)
no other explanations:
need to rule out confounds
active control of potential confounds and ensure the IV is the only variable being manipulated (experimental design)
observing/measuring potential confounds and control for them statistically (any design)
statement: the IV causes the change in DV
tips for writing clear claims:
both (or all) variables are clearly represented
clear names/labels for all variables
clear levels (values, groups, etc) of all variables
example:
warm room = not variable
room temp = variable
the relationship or difference is clearly stated
clear about correlation or causation
correlation: patience and number of traffic violations are related
causation: patience affects the number of traffic violations
validity: evidence → claims
correlation ≠ causation
inference: a conclusion made based on evidence but not directly stated in the evidence
validity: the quality of the inference made
internal validity: the quality of a cause and effect claim made by a study
stats, covariation, temporal precedence, random assignment, manipulation/control
external validity: the generalizability of a claim made by a study.
based on: sample type, size, representativeness, etc.
validity of an operational variable:
score/type on an operational variable (observation + manipulation)
variable measured/represented accurately
not the validity of the whole claim but is important for the validity of a claim
different types of evidence:
reliability: (necessary but insufficient for validity) based on data
validity: based on judgment and date
reliability of an operational variable:
reliability: consistency (not agreement)
accounts for free form random error: based on the assumption that errors are random (not correlated with any systemic factors)
assume we are measuring same group on one variable:
test retest: scores from different times should be consistent (not identical but within similar ranges)
inter-rater: scores from different raters should be consistent (various “trained” researchers/interviewers)
interviews should align
internal consistency: scores on different items should be consistent
commonly seen in peer reviewed research (method section)
asking the same factor differently should yield similar results
cronbach’s a (alpha coefficient) (need > .70)
evidence for validity summary:
face and content validity: can we infer the construct of interest based on the content of the measure
relies on judgement
construct and criterion related validity: can we infer people’s standing on the construct or an outcome based on the scores on the measure
relies on statistical analysis