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Psyc 344- Research Methods > Chapter 3: 3 Claims and 4 Validities > Flashcards

Chapter 3: 3 Claims and 4 Validities Flashcards

1
Q

What is a variable?

A

something that varies

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2
Q

What are the variable(s) and level(s) to this statement: Most students don’t know when news is fake

A
  • Variable: knowing if news is fake
  • Levels: knowing/not knowing
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3
Q

What are constants?

A
  • Something that could vary- but only has 1 level in this study
  • ex. “students don’t know when the news is fake”- students is the constant
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4
Q

What is the constant and variable in this statement: 15% of Americans smoke

A
  • Constant= Americans
  • Variable= Smoking vs not smoking
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5
Q

Manipulated vs measured variable

A
  • Measured variable: dependent variable, something you count/observe. Ex. height and IQ
  • Manipulated variable: independent variable, the research controls. Has different levels
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6
Q

Constructs/Conceptual Variables vs Operational Definitions

A
  • Constructs/Conceptual Variables- are more abstract and broadly explain your interests. Ex. coffee consumption, and happiness
  • Operational variables: aka operational definitions, defining a variable in terms you are going to use to measure it
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7
Q

How could you turn “coffee consumption” and “happiness” from constructs/conceptual variables to operational variables?

A
  • Caffeine: mg/day
  • Happiness: rank on 10 point scale
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8
Q

What is a claim?

A

The argument you are trying to make

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9
Q

What is a frequency claim?

A
  • statement about # of occurences
  • ex. 39% of teens admit to texting while driving. Screentime for children younger than 2 doubled last year. Most students/people do not know when they are reading misinformation
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10
Q

What is an association claim?

A
  • One level of one variable is related to/associated with a particular levfel of another variable
  • States a relationship between at least 2 variables- a correlation coeeficient. helps make predictions
  • ex. study links coffee consumption to lower levels of depression in women. There is no relationship between late dinner times and childhood obesity.
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11
Q

What are the 3 types of association claims?

A
  • Positive associations: as the value of one variable increases, the value of the 2nd variable also increases
  • Negative associations: as the value of one variable increases, the value of the 2nd variable decreases
  • Zero association: there really isn’t a relationship between variables
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12
Q

What is a causal claim?

A
  • A statement that says changes to one variable are responsible for changes to a second variable.
  • Makes a statement about cause and effect. Ex. Pretending to be batman makes kids stay on task.
  • Can also make a statement about lack of causal relationship. There is 0 evidence to support that vaccinations cause autism
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13
Q

What are the 3 criteria for causal claims

A
  1. Two variables must be correlated- their relationship cannot be 0
  2. The causal variable comes first and the outcome variable comes second.
  3. No other explanatory variables are present- internal validity
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14
Q

What is validity?

A
  • Correctness/Accuracy: how well a study actually measures what it is intended to study.
  • Allows inferences from study to be appropriate, meaningful, and useful
  • Several kinds of validity: Face/Internal/External/Construct
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15
Q

What is internal validity?

A
  • All about cause-and-effect
  • What causes the outcome: did changing the IV result in changes in the DV
  • Lab experiments: high in internal validity, individual differences are controlled, and the independent variable is isolated from contamination
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16
Q

Internal Validity

The 3 Musts of Causality: Co-Variation

A
  • Easiest to demonstrate
  • Says that changes in variable #1 predictably correspond to changes in variable #2
  • Showing presence of correlation
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17
Q

Internal Validity

The 3 Musts of Causality: Temporal precedence

A
  • Says that changes in the IV always precede changes in the DV
  • Your manipulation must come before the change in behavior
18
Q

Internal Validity

The 3 Musts of Causality: Third Variable Problem/Eliminating Confounds

A
  • Third Variable Problem: creates a false appearance of a causal relationship. Ex. Ice cream sales and violent crime, Intelligence and shoe size
  • So need to eliminate confounds: having a control group and doing the experiment double blind helps
19
Q

Internal Validity

Experimental Design

A
  • Best suited to show causality
  • Manipulate IV, Control confounds, carefully define DV
  • Great for Internal validity, but not as great for external validity (as IV increases, EV decreases)
20
Q

What is external validity?

A
  • Generalizability: extent to which study results apply to other settings, people, social settings, and cultures
  • With respect to people: will results seen in one sample occur in another sample? Seen in different ages, genders, and groups?
21
Q

External validity- generalizability

A
  • Will results seen in one setting occur in another setting?
  • Natural vs contrived
  • Home vs school
22
Q

“Can’t be delicious and nutritious”

A
  • Can’t have high external and high internal validity in one study
  • Passive observation or active manipulation
23
Q

What is the construct in construct validity?

A
  • Theoretical, intangible quality, trait, mental process, on which individuals differ
  • Examples include: leadership ability, depression, intelligence, and love
24
Q

What is construct/conceptual validity?

A
  • Construct validity is the idea that the IVs and DVs truly represent the constructs being studied or measured.
  • Based on quality of operational definitions
25
Q

Construct Validity: “Makes research fun and challenging”

A
  • Coming up with good ways to measure elusive things
  • Example self-esteem: positive attitude of self, competence/likeability, stable/variable trait
26
Q

What is conceptual validity?

A
  • How well the hypothesis fits the theory- How well it follows logically from the theory and appropriately “maps onto” the theory
  • Also about if interest in this hypothesis or research question warrranted?
27
Q

What is reliability in research?

A
  • Consistency of measurement over time
  • Is what you’re studying driven by stable attributes, traits, and individual differences
  • How good the study/measure is at producing similar results w/ repeated exposure to the same persons under similar circumstances
28
Q

Is reliability the same as validity

A

NO

29
Q

What are the kinds of reliability

A
  • inter-rater/inter-observed, internal consistency, and test-retest
30
Q

What is test-retest reliability?

A
  • Same measure/manipulation, twice
  • How consistent study results are when study is executed multiple times?
  • You expose the same group to the same study several times, the 2nd outcome should be predictable based on the first
31
Q

Test-Retest Reliability: Beware of maturation

A
  • Expect lower test-retest reliability as more time passes between 2 studies. Because people change over time- raoidly changing traits and way of life/frame of mind
32
Q

When is the ideal re-test window?

A

2 to 4 weeks

33
Q

reliability

Internal consistency

A
  • consistency inside the measure
  • How well all parts of a study measure contribute meaningfully to the measure
  • To fix the problem: give 2 alternate forms versions of same measure to same group (how much someone loves and hates the same thing) or “split-half” the test and correlate the scores on each half
34
Q

What is inter-rater reliability?

A
  • The degree of agreement
  • Multiple independent researchers judge/quantify each participant’s outcome score without confering with each other. (like judges in the olympics)
  • Need time to train judges- they must understand and follow the rules for coding the outcome
35
Q

inter-rater reliability

When is degree of agreement really useful?

A
  • When you can’t use self-rating to measure the construct
  • when there are highly subjective measures of construct

ex. break dancing in olympics

36
Q

More is better

A
  • Better representativeness
  • Results are more reliable with more observations, measures, and observers
  • More data=less error, and is a better reflection of the construct you are studying
  • Results are also more valid- closer approximation of the actual/true relationship or phenomenon. Our sample comes closer to representing the population
37
Q

Discrete variables

A
  • separate/nondivisible categories
  • no values between adjacent categories
  • whole countable values
  • Qualitative categories
  • Ex. # of kids or cars you have
  • Good for frequency statements
38
Q

Continuous Variables

A
  • Has infinite number of values
  • Any number with fractional parts
  • no fixed categories
  • divided in many ways
  • Ex. height, weight, velocity, minutes
39
Q

Scales of Measurement

Nominal

A
  • set of categories with different names, only count frequency
  • don’t describe direction or size of difference
  • Examples: What car you own, academic major
40
Q

Scales of Measurement

Ordinal

A
  • categories w/ different magnitude
  • describe rank/sequential direction/order
  • do not describe the size of the interval
  • Ex. gold/silver/bronze, small/med/large
41
Q

Scales of Measurement

What do interval and ratio scales have in common?

A
  • both have intervals of exactly the same size (ordered categories w sequential intervals)
  • Both tell us size and direction of change
42
Q

Scales of Measurement

What is different between ratio and interval scales?

A
  • Ratio: has absolute zero point. 0= complete absence of construct. Allows for ratio comparisons (2x as many beers, 5x as much pizza)
  • Interval: has arbitrary Zero point. 0 for convenience/references. Cannot do ratio comparisons. (ex. temperature and golf score)

Psyc 344- Research Methods (4 decks)

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